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1
Saiapina, Inna, Mykhailo Babaiev, and Olha Аnanіevа. "Reducing noise influence on an audio frequency track circuit." MATEC Web of Conferences 294 (2019): 03015. http://dx.doi.org/10.1051/matecconf/201929403015.
Повний текст джерелаАнотація:
In connection with electromagnetic interference influence on the track circuits, the purpose of the research is finding the means to increase the noise immunity of an audio frequency track circuit. The authors propose a new engineering solution, which enables reducing the effect of noises on the input of the track receiver in the intervals between signal current pulses. The proposed noise-immune audio frequency track circuit is based on inserting a delay line, an adjustable single-pulse generator and a controlled electronic switch into the existing audio frequency track circuit equipment. To analyze its efficiency, the operation of the audio frequency track circuit was simulated under conditions of traction current disturbances, impulse and fluctuation interferences with the known parameters. The results show that proposed device for railway transport allows to increase a signal-to-noise ratio on the track receiver input from 8% to 30%, depending on the interference parameters and the level of the useful signal.
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Sokolov, Sergei A., and Yuri A. Kovalgin. "INFLUENCE OF THE COMPRESSION ALGORITHMS ON THE QUALITY OF AUDIO PROGRAMS IN DRM DIGITAL RADIO BROADCASTING SYSTEM." T-Comm 15, no. 7 (2021): 4–13. http://dx.doi.org/10.36724/2072-8735-2021-15-7-4-13.
Повний текст джерелаАнотація:
This work studied the influence of MPEG-4 HE-AAC v.2 and MPEG-4 xHE-AAC compression algorithms on the reproduction performance of high-quality audio signals. The first part of the article is based on the analysis of earlier publications, studied quality of the compression algorithms for MPEG-4 ISO/IEC 14493-3 (AAC, AAC+SBR, PS, AAC+SBR+PS) and MPEG D Surround standards applied in MPEG-4 HE-AAC v.2 and MPEG-4 xHE-AAC codecs of DAB and DRM systems for digital audio broadcasting, respectively. It has been demonstrated that their use for processing of high-quality audio signals in the frequency range of 40…15000 Hz, allowed to reduce the digital-data rate at the output to 24…30 êbit/s, without observing noticeable phenomena. This conclusion was confirmed in the second part of the article, which described the results of relative comparison of the quality of reproduction of audio signals broadcasted via analogues FM or digital DRM channels. The equipment employed for their realization was described, as well as the methodology to obtain test recordings in order to perform the statistical data analysis. Further, the specific data scales were shown to evaluate the signal pairs being compared. Results of the experiments and their analysis confirmed that, for a digital data rate of 30 êbit/s obtained at the output of the MPEG-4 xHE-AAC coder, the difference in quality was rather weak for audio signals ranging from 40 to 15000 Hz, broadcasted via both analogues and digital channels. In addition, only a marginal difference was noticed for the signal pairs received from the digital output channels of the transmitter processor and DRM receiver. It has been demonstrated that the MPEG-4 xHE-AAC codec, compared to the previous MPEG-4 HE-AAC v.2 version, exhibited clear advantages for practical applications in terms of sound quality. Based on the gained experience, common criteria of deterioration of the data quality were formulated and generalized for all audio compression MPEG standards.
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Chen, Bo, Heung Kou, Bowen Hou, and Yanbing Zhou. "Music Feature Extraction Method Based on Internet of Things Technology and Its Application." Computational Intelligence and Neuroscience 2022 (April 18, 2022): 1–10. http://dx.doi.org/10.1155/2022/8615152.
Повний текст джерелаАнотація:
Due to the influence of factors such as strong music specialization, complex music theory knowledge, and various variations, it is difficult to identify music features. We have developed a music characteristic identification system using the Internet-based method. The physical sensing layer of our designed system deploys audio sensors on various coordinates to capture the raw audio signal and performs audio signal processing and analysis using the TMS320VC5402 digital signal processor; the Internet transport layer places audio sensors at various locations to capture the raw audio signal. The TMS320VC5402 digital signal processor is used for audio signal diagnosis and treatment. The network transport layer transmits the finished audio signal to the data base of song signal in the application layer of the system; the song characteristic analysis block in the application layer adopts dynamics. The music characteristic analysis block in the applied layer adopts dynamic time warping algorithm to acquire the maximal resemblance between the test template and the reference template to achieve music signal characteristic identification and identify music tunes and music modes based on the identification results. The application layer music feature analysis block adopts dynamic time regularization algorithm and mel-frequency cepstrum coefficient to achieve music signal feature recognition and identify music tunes and music patterns based on the recognition results. We have verified through experiments, and the results show that the system operates consistently, can obtain high-quality music samples, and can extract good music characteristics.
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Sarno, Riyanarto, Johanes Andre Ridoean, Dwi Sunaryono, and Dedy Rahman Wijaya. "Classification of Music Mood Using MPEG-7 Audio Features and SVM with Confidence Interval." International Journal on Artificial Intelligence Tools 27, no. 05 (August 2018): 1850016. http://dx.doi.org/10.1142/s0218213018500161.
Повний текст джерелаАнотація:
Psychologically, music can affect human mood and influence human behavior. In this paper, a novel method for music mood classification is introduced. In the experiment, music mood classification was performed using feature extraction based on MPEG-7 features from the ISO/IEC 15938 standard for describing multimedia content. The result of this feature extraction are 17 low-level descriptors. Here, we used the Audio Power, Audio Harmonicity, and Audio Spectrum Projection features. Moreover, the discrete wavelet transform (DWT) was utilized for audio signal reconstruction. The reconstructed audio signals were classified by the new method, which uses a support vector machine with a confidence interval (SVM-CI). According to the experimental results, the success rate of the proposed method was satisfactory and SVM-CI outperformed the ordinary SVM.
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Garcia, Jane Mertz, and Michael P. Cannito. "Influence of Verbal and Nonverbal Contexts on the Sentence Intelligibility of a Speaker With Dysarthria." Journal of Speech, Language, and Hearing Research 39, no. 4 (August 1996): 750–60. http://dx.doi.org/10.1044/jshr.3904.750.
Повний текст джерелаАнотація:
The influence of verbal and nonverbal contextual factors on intelligibility was examined using sentences produced under varying conditions by a speaker with severe flaccid dysarthria. Contextual factors included (a) concurrent production of communication gestures, (b) predictiveness of message content, (c) relatedness of sentences to specific situational contexts, and (d) prior familiarization with the speaker. Sentences produced by the speaker were audio- and video-recorded and presented to 96 listeners/viewers who were assigned to three different methods of presentation of the stimuli: (a) audio + video, (b) audio-only, or (c) video-only conditions. Results indicated that gestures, predictiveness, and context influenced intelligibility; however, complex interactions were observed among these factors and methods of presentation of the stimuli. Results were interpreted in light of Lindblom's "mutuality model," indicating that when signal fidelity is poor, as in the present speaker with dysarthria, differing combinations of signal-independent information may be employed to enhance listener understanding of spoken messages.
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Bang, Woorim, and Ji Won Yoon. "Power Grid Estimation Using Electric Network Frequency Signals." Security and Communication Networks 2019 (September 24, 2019): 1–11. http://dx.doi.org/10.1155/2019/1982168.
Повний текст джерелаАнотація:
The electric network frequency (ENF) has a statistical uniqueness according to time and location. The ENF signal is always slightly fluctuating for the load balance of the power grid around the fundamental frequency. The ENF signals can be obtained from the power line using a frequency disturbance recorder (FDR). The ENF signal can also be extracted from video files or audio files because the ENF signal is also saved due to the influence of the electromagnetic field when video files or audio files are recorded. In this paper, we propose a method to find power grid from ENF signals collected from various time and area. We analyzed ENF signals from the distribution level of the power system and online uploaded video files. Moreover, a hybrid feature extraction approach, which employs several features, is proposed to infer the location of the signal belongs regardless of the time that the signal was collected. Employing our suggested feature extraction methods, the signal which extracted from the power line can be classified 95.21% and 99.07% correctly when ENF signals have 480 and 1920 data points, respectively. In the case of ENF signals extracted from multimedia, the accuracy varies greatly according to the recorded environment such as network status and microphone quality. When constructing a feature vector from 120 data points of ENF signals, we could identify the power grid had an average of 94.17% accuracy from multimedia.
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Hanzlik, Tomasz. "Class D audio amplifier and method for compensation of power supply voltage influence on output audio signal in class D audio amplifier." Journal of the Acoustical Society of America 120, no. 5 (2006): 2400. http://dx.doi.org/10.1121/1.2395103.
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Kropotov, Y. A., A. A. Belov, and A. Y. Prockuryakov. "Increasing signal/acoustic interference ratio in telecommunications audio exchange by adaptive filtering methods." Information Technology and Nanotechnology, no. 2416 (2019): 271–76. http://dx.doi.org/10.18287/1613-0073-2019-2416-271-276.
Повний текст джерелаАнотація:
The paper deals with the issues of increasing signal/noise ratio in telecommunication audio exchange systems. The study of characteristics of speech signals and acoustic noises, such as mathematical expectation, dispersion, relative intensity of acoustic speech signals and various types of acoustic noises and interference is carried out. It is shown that in the design of telecommunications systems, in particular loudspeaker systems operating under the influence of external acoustic noise of high intensity, it is necessary to solve the problem of developing algorithms to effectively suppress the above mentioned interference to ensure the necessary signal/noise ratio in communication systems. A mathematical model of the autocorrelation function of the speech signal by using the Lagrange interpolation polynomial of order 10, considered the creation of adaptive algorithms to suppress acoustic noise by linear filtering methods. Thus suppression of acoustic noises and hindrances is possible at the expense of operated change of area of a cutting in the interval from 0 Hz to 300-1000 Hz, depending on a hindrance conditions.
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Přibil, Jiří, Anna Přibilová, and Ivan Frollo. "Analysis of Energy Relations between Noise and Vibration Signals in the Scanning Area of an Open-Air MRI Device." Proceedings 4, no. 1 (November 14, 2018): 29. http://dx.doi.org/10.3390/ecsa-5-05730.
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The paper analyzes the influence of different magnetic resonance (MR) scan sequence parameters (echo time, repetition time, orientation of scan slices, sequence type, mass of a tested object) on the energy of the produced noise and vibration. The measured sound pressure levels, together with the recorded noise and vibration signals, were stored in a database and then processed using similar methods to speech signal analysis because the main frequencies of the acoustic noise and vibration lie in the standard audio frequency range. In the signal processing phase, four types of parameters describing the signal energy were determined and statistically analyzed, and the obtained results were visually and numerically compared.
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Oruganti, Rakesh. "Detecting and Analyzing Emotions Using Text Stream Messages." ECS Transactions 107, no. 1 (April 24, 2022): 16913–23. http://dx.doi.org/10.1149/10701.16913ecst.
Повний текст джерелаАнотація:
Emotions are the gateway to converse your point of view to others. Generally, you can express your emotions either by audio or writing or symbols. Amid of audio and writing, audio/voice is a persuasive method to communicate emotions. During this work, we can get these emotions through the audio of the human using a deep learning network. We are extensively classify the emotions of the humans into irate, quiet, disdain, dread, glad, nonpartisan, miserable, and shock for effective emotion prediction. The audio features define how the audio signal reacts to the disturbing influence perceptible throughout. Thus, these features play a vital role in recognizing the emotion in audio. We are applying MFCC (Mel-Frequency Cepstral Coefficients) to the audio information to extract these essential features. MFCC is the preeminent method to extract the features from audio. Moreover, to get exact features, we are applying increase methods to the audio information.
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Browarska, Natalia, Aleksandra Kawala-Sterniuk, Jaroslaw Zygarlicki, Michal Podpora, Mariusz Pelc, Radek Martinek, and Edward Gorzelańczyk. "Comparison of Smoothing Filters’ Influence on Quality of Data Recorded with the Emotiv EPOC Flex Brain–Computer Interface Headset during Audio Stimulation." Brain Sciences 11, no. 1 (January 13, 2021): 98. http://dx.doi.org/10.3390/brainsci11010098.
Повний текст джерелаАнотація:
Off-the-shelf, consumer-grade EEG equipment is nowadays becoming the first-choice equipment for many scientists when it comes to recording brain waves for research purposes. On one hand, this is perfectly understandable due to its availability and relatively low cost (especially in comparison to some clinical-level EEG devices), but, on the other hand, quality of the recorded signals is gradually increasing and reaching levels that were offered just a few years ago by much more expensive devices used in medicine for diagnostic purposes. In many cases, a well-designed filter and/or a well-thought signal acquisition method improve the signal quality to the level that it becomes good enough to become subject of further analysis allowing to formulate some valid scientific theories and draw far-fetched conclusions related to human brain operation. In this paper, we propose a smoothing filter based upon the Savitzky–Golay filter for the purpose of EEG signal filtering. Additionally, we provide a summary and comparison of the applied filter to some other approaches to EEG data filtering. All the analyzed signals were acquired from subjects performing visually involving high-concentration tasks with audio stimuli using Emotiv EPOC Flex equipment.
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Kropotov, Yu A., A. A. Belov, A. A. Kolpakov, and A. Yu Proskuryakov. "The syllable intelligibility in the system of information transmission by speech signals depending on the intensity of acoustic noise." Information Technology and Nanotechnology, no. 2416 (2019): 277–82. http://dx.doi.org/10.18287/1613-0073-2019-2416-277-282.
Повний текст джерелаАнотація:
The paper investigates the effect of the signal-to-noise ratio on syllable intelligibility under the intense influence of external acoustic interference when exchanging voice messages in telecommunication systems of public address systems. The article discusses the effect on the syllable intelligibility of the signal / external acoustic noise ratio, examines the effect of the integral articulation index, the dependence of the perception coefficient of formants on the relative level of formant intensity, the dependence of the formant parameter on the geometric mean frequency of the i-th spectrum of the speech signal. In accordance with the results of studies of the integral articulation index depending on the signal-to-noise ratio, a function of syllable intelligibility depending on the signal-to-noise ratio was obtained, using which it is possible to determine the maximum value of the output signal-to-noise ratio in the audio exchange telecommunications system to obtain a given syllable intelligibility. At the same time, experimentally determined the value of the signal-to-noise ratio in the telecommunications system of audio exchange to obtain a syllable intelligibility of at least 93% for ensure full perception of the transmitted speech information.
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Garcia, Jane Mertz, and Paul A. Dagenais. "Dysarthric Sentence Intelligibility." Journal of Speech, Language, and Hearing Research 41, no. 6 (December 1998): 1282–93. http://dx.doi.org/10.1044/jslhr.4106.1282.
Повний текст джерелаАнотація:
This study examined changes in the sentence intelligibility scores of speakers with dysarthria in association with different signal-independent factors (contextual influences). This investigation focused on the presence or absence of iconic gestures while speaking sentences with low or high semantic predictiveness. The speakers were 4 individuals with dysarthria, who varied from one another in terms of their level of speech intelligibility impairment, gestural abilities, and overall level of motor functioning. Ninety-six inexperienced listeners (24 assigned to each speaker) orthographically transcribed 16 test sentences presented in an audio + video or audio-only format. The sentences had either low or high semantic predictiveness and were spoken by each speaker with and without the corresponding gestures. The effects of signal-independent factors (presence or absence of iconic gestures, low or high semantic predictiveness, and audio + video or audio-only presentation formats) were analyzed for individual speakers. Not all signal-independent information benefited speakers similarly. Results indicated that use of gestures and high semantic predictiveness improved sentence intelligibility for 2 speakers. The other 2 speakers benefited from high predictive messages. The audio + video presentation mode enhanced listener understanding for all speakers, although there were interactions related to specific speaking situations. Overall, the contributions of relevant signal-independent information were greater for the speakers with more severely impaired intelligibility. The results are discussed in terms of understanding the contribution of signal-independent factors to the communicative process.
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Heo, Woon-Haeng, Hyemi Kim, and Oh-Wook Kwon. "Integrating Dilated Convolution into DenseLSTM for Audio Source Separation." Applied Sciences 11, no. 2 (January 15, 2021): 789. http://dx.doi.org/10.3390/app11020789.
Повний текст джерелаАнотація:
Herein, we proposed a multi-scale multi-band dilated time-frequency densely connected convolutional network (DenseNet) with long short-term memory (LSTM) for audio source separation. Because the spectrogram of the acoustic signal can be thought of as images as well as time series data, it is suitable for convolutional recurrent neural network (CRNN) architecture. We improved the audio source separation performance by applying the dilated block with a dilated convolution to CRNN architecture. The dilated block has the role of effectively increasing the receptive field in the spectrogram. In addition, it was designed in consideration of the acoustic characteristics that the frequency axis and the time axis in the spectrogram are changed by independent influences such as speech rate and pitch. In speech enhancement experiments, we estimated the speech signal using various deep learning architectures from a signal in which the music, noise, and speech were mixed. We conducted the subjective evaluation on the estimated speech signal. In addition, speech quality, intelligibility, separation, and speech recognition performance were also measured. In music signal separation, we estimated the music signal using several deep learning architectures from the mixture of the music and speech signal. After that, the separation performance and music identification accuracy were measured using the estimated music signal. Overall, the proposed architecture shows the best performance compared to other deep learning architectures not only in speech experiments but also in music experiments.
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Weychan, Radoslaw, Tomasz Marciniak, Agnieszka Stankiewicz, and Adam Dabrowski. "Real Time Recognition Of Speakers From Internet Audio Stream." Foundations of Computing and Decision Sciences 40, no. 3 (September 1, 2015): 223–33. http://dx.doi.org/10.1515/fcds-2015-0014.
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Abstract In this paper we present an automatic speaker recognition technique with the use of the Internet radio lossy (encoded) speech signal streams. We show an influence of the audio encoder (e.g., bitrate) on the speaker model quality. The model of each speaker was calculated with the use of the Gaussian mixture model (GMM) approach. Both the speaker recognition and the further analysis were realized with the use of short utterances to facilitate real time processing. The neighborhoods of the speaker models were analyzed with the use of the ISOMAP algorithm. The experiments were based on four 1-hour public debates with 7–8 speakers (including the moderator), acquired from the Polish radio Internet services. The presented software was developed with the MATLAB environment.
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Bartusiak, Emily R., and Edward J. Delp. "Frequency Domain-Based Detection of Generated Audio." Electronic Imaging 2021, no. 4 (January 18, 2021): 273–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.4.mwsf-273.
Повний текст джерелаАнотація:
Attackers may manipulate audio with the intent of presenting falsified reports, changing an opinion of a public figure, and winning influence and power. The prevalence of inauthentic multimedia continues to rise, so it is imperative to develop a set of tools that determines the legitimacy of media. We present a method that analyzes audio signals to determine whether they contain real human voices or fake human voices (i.e., voices generated by neural acoustic and waveform models). Instead of analyzing the audio signals directly, the proposed approach converts the audio signals into spectrogram images displaying frequency, intensity, and temporal content and evaluates them with a Convolutional Neural Network (CNN). Trained on both genuine human voice signals and synthesized voice signals, we show our approach achieves high accuracy on this classification task.
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Naida, S. A., Y. O. Onykienko, O. I. Drozdenko, O. I. Smolenska, V. S. Baran, and N. O. Iakunina. "Analysis of the influence of load inductance on nonlinear distortions of a class D amplifier caused by «dead time»." Electrical Engineering & Electromechanics, no. 3 (June 23, 2021): 32–37. http://dx.doi.org/10.20998/2074-272x.2021.3.05.
Повний текст джерелаАнотація:
Goal. Analysis of the effect of load inductance at the output of the class D amplifier for different values of the duration of «dead time» and assessment of the adequacy of existing mathematical models for calculating the THD at the output of the amplifier depending on the duration of «dead time». Methodology. The study of the effect of «dead time» on the THD was performed using a computer model of the half-bridge converter board EPC9035 from Efficient Power Conversion. This board contains GaN transistors EPC2022 eGaN®, the corresponding control driver and other necessary elements for operation. The use of GaN transistors has made it possible to investigate the operation in a wide range of frequent switching, both to control the motor and to amplify the audio signal. Results. It is established that the value of load inductance affects the level of nonlinear distortions caused by «dead time». At inductance values that provide a constant sign of the output current, a difference arises between the duration of the input and output pulses, which increases the THD. At inductance values, when the choke current changes sign during a pulse, there is no error between the duration of the input and output pulses. Changing the inductance changes the relationship between the error signal and the non-error signal. THD changes accordingly. At high conversion frequencies, the voltage spikes caused by the choke current through the built-in diodes during the dead time are partially compensated by overcharging the output capacitance of the transistors, which also reduces harmonic distortion. Originality. For the first time, the value of the THD at the outlets in the fallowness of the different indices of the inductance of the choke and the theoretical calculation of the value in the results of the computer model was obtained. Practical significance. The dependence of the THD values on the inductance of the choke for converters with a switching frequency range from 1 kHz to 400 kHz, which allows them to be used both to control the motor and to amplify the audio signal.
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Zhou, De Xin, Ming Yu Song, and Teng Da Ma. "Research of AMU Unit Fault Testability Based on Multi-Signal Modeling and Fuzzy Decision." Advanced Materials Research 760-762 (September 2013): 1089–94. http://dx.doi.org/10.4028/www.scientific.net/amr.760-762.1089.
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The Multi-signal Flow Graph (MFG) is a simple and effective system modeling methodology, widely used in testability analysis and fault diagnosis field. In order to shorten the maintenance time and reduce the influence of human factors, the MFG method was introduced, and it was used to set up the testability model of aircraft Audio Management Unit (AMU) and found the fault-testability dependency matrix and the fault-fault dependency matrix. Based on dependency matrix and real unit fault message, the trapezoidal fuzzy number algorithm was introduced, thus the new fault diagnosis method was generated. Finally, an example proves that the fault diagnosis algorithm can not only locate the fault more accurately, but also improve the maintenance efficiency.
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Stacey, Jemaine E., Christina J. Howard, Suvobrata Mitra, and Paula C. Stacey. "Audio-visual integration in noise: Influence of auditory and visual stimulus degradation on eye movements and perception of the McGurk effect." Attention, Perception, & Psychophysics 82, no. 7 (June 12, 2020): 3544–57. http://dx.doi.org/10.3758/s13414-020-02042-x.
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AbstractSeeing a talker’s face can aid audiovisual (AV) integration when speech is presented in noise. However, few studies have simultaneously manipulated auditory and visual degradation. We aimed to establish how degrading the auditory and visual signal affected AV integration. Where people look on the face in this context is also of interest; Buchan, Paré and Munhall (Brain Research, 1242, 162–171, 2008) found fixations on the mouth increased in the presence of auditory noise whilst Wilson, Alsius, Paré and Munhall (Journal of Speech, Language, and Hearing Research, 59(4), 601–615, 2016) found mouth fixations decreased with decreasing visual resolution. In Condition 1, participants listened to clear speech, and in Condition 2, participants listened to vocoded speech designed to simulate the information provided by a cochlear implant. Speech was presented in three levels of auditory noise and three levels of visual blurring. Adding noise to the auditory signal increased McGurk responses, while blurring the visual signal decreased McGurk responses. Participants fixated the mouth more on trials when the McGurk effect was perceived. Adding auditory noise led to people fixating the mouth more, while visual degradation led to people fixating the mouth less. Combined, the results suggest that modality preference and where people look during AV integration of incongruent syllables varies according to the quality of information available.
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Hustad, Katherine C., and Jane Mertz Garcia. "Aided and Unaided Speech Supplementation Strategies." Journal of Speech, Language, and Hearing Research 48, no. 5 (October 2005): 996–1012. http://dx.doi.org/10.1044/1092-4388(2005/068).
Повний текст джерелаАнотація:
Purpose: This study compared the influence of speaker-implemented iconic hand gestures and alphabet cues on speech intelligibility scores and strategy helpfulness ratings for 3 adults with cerebral palsy and dysarthria who differed from one another in their overall motor abilities. Method: A total of 144 listeners (48 per speaker) orthographically transcribed sentences spoken with alphabet cues (aided), iconic hand gestures (unaided), and a habitual speech control condition; scores were compared within audio-visual and audio-only listening formats. Results: When listeners were presented with simultaneous audio and visual information, both alphabet cues and hand gestures resulted in higher intelligibility scores and higher helpfulness ratings than the no-cues control condition for each of the 3 speakers. When listeners were presented with only the audio signal, alphabet cues and gestures again resulted in higher intelligibility scores than no cues for 2 of the 3 speakers. Temporal acoustic analyses showed that alphabet cues had consistent effects on speech production, including reduced speech rate, reduced articulation rate, and increased frequency and duration of pauses. Findings for gestures were less consistent, with marked differences noted among speakers. Conclusions: Results illustrate that individual differences play an important role in the value of supplemental augmentative and alternative communication strategies and that aided and unaided strategies can have similar positive effects on the communication of speakers with global motor impairment.
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Xu, Yulan, and Qiaowei Li. "Music Classification and Detection of Location Factors of Feature Words in Complex Noise Environment." Complexity 2021 (April 20, 2021): 1–12. http://dx.doi.org/10.1155/2021/5518967.
Повний текст джерелаАнотація:
In order to solve the problem of the influence of feature word position in lyrics on music emotion classification, this paper designs a music classification and detection model in complex noise environment. Firstly, an intelligent detection algorithm for electronic music signals under complex noise scenes is proposed, which can solve the limitations existing in the current electronic music signal detection process. At the same time, denoising technology is introduced to eliminate the noise and extract the features from the signal. Secondly, from the perspective of audio and lyrics of song sentiment analysis and the unique characteristics of lyrics text, a lyric sentiment analysis method based on text title and position weight is proposed. Finally, considering the influence of the weight of feature words in different positions on the classification of lyrics, the analytic hierarchy process is used to calculate the weight of feature words in different positions of text title and lyrics before, in, and after the text. The results show that in the complex noise environment, the accuracy of music classification and detection of the proposed model is more than 90%, which is far beyond the control range of the actual application of music processing. The effect of music classification and detection is better than that of the contrast model, which has a certain practical application value.
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Boyarkina, Iren. "Positive influence of certain sports on learning and second language acquisition processes." Zbornik radova Filozofskog fakulteta u Pristini 51, no. 1 (2021): 309–20. http://dx.doi.org/10.5937/zrffp51-30724.
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Various research convincingly demonstrated positive influence of certain sports and physical exercises on brain and brain functions in general, and on cognitive functions in particular. As it has been demonstrated, efficient and well-developed cognitive functions enhance all human activities and are of crucial importance for learning. In particular, this paper focuses on the positive correlation between certain sports and language learning and its relevance to the Second Language Acquisition studies (SLA). In SLA, students' ability to process input strongly depends on their cognitive abilities, namely, their abilities to process audio and visual input. As various researchers demonstrated, some sports enhance sportsmen's abilities of audio and visual perception; these developed cognitive abilities may, in turn, enhance SLA process. The paper analyses some data collected during the experiments with three groups of students, age 20-23: basketball players, judo wrestlers and control group whose members practiced sports only 2h/week. Three groups were exposed to three types of stimuli: (reverse chess pattern, tone click, flash of light); their brain activity was monitored by EEG. The obtained results demonstrated that basketball players manifested better-developed cognitive abilities responsible for the perception of audio and video stimuli. They were also faster in making decisions on the basis of the video/audio stimuli perceived. Similar results were obtained by American psychologists (University of Illinois, Urbana-Champaign). Their study involved 87 Brazilian volleyball players and 67 persons who don't practice sports. The results were published in Frontiers in Psychology. Experiments have shown that athletes are usually better in controlling their reactions and are able to slow down their reactions, if necessary. According to the professor of Psychology Arthur Kramer, one of the authors of the research, "Athletes can perceive information faster and switch quicker between different tasks than those who don't practice sports." During the experiment, all the participants were asked to perform tasks to test their cognitive abilities (information perception, memory, reactions). The most interesting discovery was that the athletes had significant cognitive advantages over women and men who had not practiced sports. Volleyball players were faster in reactions, in noticing differences in the pictures, in identifying the missing details in puzzles. The process of auditory and visual perception and processing involves many neural structures: from primary units of signal processing sensors to higher levels of processing, responsible for stimuli recognition and decision-making. As it is known, individual waves of cognitive evoked potentials reflect the involvement of certain neural mechanisms of visual and auditory systems in processing and recognition of stimuli of corresponding modality. Wave characteristics can indirectly indicate working speed of specific units of the neural circuit and the number of neurons involved; it may allow measuring the influence of various sports training loads on the development of neural chains involved in audio/video stimuli perception, processing and decision-making. These aspects are also considered important for input processing in SLA. The paper analyses positive contribution of certain sports to learning in general, and Second Language Acquisition in particular, using neuroscience, psychological and socio-cultural approaches.
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Petrović, Nikola, Miloš Bjelić, Jelena Ćertić, Miodrag Stanojević, and Dragana Šumarac-Pavlović. "Analyses of decimation filter stopband attenuation influence on subjective quality of audio signals." Telfor Journal 10, no. 2 (2018): 86–90. http://dx.doi.org/10.5937/telfor1802086p.
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Pausch, Florian, Gottfried Behler, and Janina Fels. "SCaLAr – A surrounding spherical cap loudspeaker array for flexible generation and evaluation of virtual acoustic environments." Acta Acustica 4, no. 5 (2020): 19. http://dx.doi.org/10.1051/aacus/2020014.
Повний текст джерелаАнотація:
Introduction: Surrounding spherical loudspeaker arrays facilitate the application of various spatial audio reproduction methods and can be used for a broad range of acoustic measurements and perceptual evaluations. Methods: Installed in an anechoic chamber, the design and implementation of such an array of 68 coaxial loudspeakers, sampling a spherical cap with a radius of 1.35 m on an equal-area grid, is presented. A network-based audio backbone enables low-latency signal transmission with low-noise amplifiers providing a high signal-to-noise ratio. To address batch-to-batch variations, the loudspeaker transfer functions were equalised by individually designed 512-taps finite impulse response filters. Time delays and corresponding level adjustments further helped to minimise radial mounting imperfections. Results: The equalised loudspeaker transfer functions measured under ideal conditions and when mounted, their directivity patterns, and in-situ background noise levels satisfy key criteria towards applicability. Advantages and shortcomings of the selected decoders for panning-based techniques, as well as the influence of loudspeaker positioning errors, are analysed in terms of simulated performance metrics. An evaluation of the achievable channel separation allows deriving recommendations of feasible subset layouts for loudspeaker-based binaural reproduction. Conclusion: The combination of electroacoustic properties, simulated sound field synthesis performance and measured channel separation classifies the system as suitable for its target applications.
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Hao, Jianhong. "Optimizing the Design of a Vocal Teaching Platform Based on Big Data Feature Analysis of the Audio Spectrum." Wireless Communications and Mobile Computing 2022 (May 9, 2022): 1–9. http://dx.doi.org/10.1155/2022/9972223.
Повний текст джерелаАнотація:
With the development of electronics and communication technology, digital audio processing technologies such as digital audio broadcasting and multimedia communication have been widely used in society, and their influence on people’s lives has become increasingly profound. At present, the real-time and accuracy of musical instrument tuners on the market need to be improved, which hinders the design of vocal music teaching system. Based on the BP neural network algorithm and fast Fourier transform algorithm in FPGA, this paper designs a real-time and efficient audio spectrum analysis system, which realizes the spectrum analysis function of music signal. The methods to calculate fast discrete Fourier transform are the FFT algorithm based on time extraction and the FFT algorithm based on frequency extraction. The characteristic of BP neural network algorithm is that it can not only obtain the corresponding estimation results by forward propagation of the input data but also carry out back propagation from the output layer according to the error between the estimation results and the actual results, so as to optimize the connection weight between each layer. This paper proposes to add Nios II system to FPGA processor and adopt cyclone IV in the hardware design of the system, which can be better compatible with the system designed in this paper. In the software part, WM8731 is used to process the audio data. WM8731 consumes very little power to the system, which will effectively improve the processing efficiency of the system. Compared with the original system, the data model obtained after screening and processing of the system model designed in this paper has an algorithm accuracy of more than 90%, among which the audio spectrum clarity of vocal music can reach 95%. Based on the above, the circuit of each module is tested, and in the specific experimental process, the audio frequency spectrum under different conditions is analyzed and data processed. The system can complete the collection and analysis of various music signals in real time, overcome the limitation of single function of traditional tuner, improve the utilization rate of tuner and the clarity of timbre, and also tune a variety of musical instruments and greatly improve the intonation of musical instruments and the utilization rate of tuner, which has a certain practical value.
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LUZHANSKIY, Viktor, Lesia KARPOVA, and Maksym KANYUKA. "INFLUENCE OF THE TRANSMISSION RATE OF DIGITAL INFORMATION STREAMS IN VSAT-BASED SATELLITE COMMUNICATION NETWORKS WITH APPROPRIATE SIGNAL-TO-NOISE RATIOS ON THE PROBABILITY OF BIT ERROR." Herald of Khmelnytskyi National University 303, no. 6 (December 2021): 207–15. http://dx.doi.org/10.31891/2307-5732-2021-303-6-207-215.
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Among the satellite technologies, special attention is paid to the development of satellite communication technologies based on VSAT (Very Small Aperture Terminal). Small ground station VSAT, a terminal with a very small antenna diameter (0.9 … 3.5 m), allows the use of VSAT stations antennas. This makes it possible to significantly reduce the size and cost of ground stations, the power of their transmitters and make their use widespread. VSAT equipment makes it possible to build multiservice networks that provide all modern communication services: Internet access; telephone connection; transmission of audio and video information; reservation of existing communication channels; data collection, monitoring and remote control of industrial facilities, etc. Satellite signals, especially high-frequency bands Ku and Ka, are subject to attenuation during rain, fog, clouds. But this shortcoming is easily overcome when properly designing the network, choosing the technology and location of antennas. The scientific article is devoted to the study of the influence of the speed of digital information transmission in satellite networks based on VSAT – a small satellite ground station, at the appropriate signal-to-noise ratio at the input of the receiver of the subscriber satellite station on the probability of bit error. The technical characteristics of subscriber satellite stations operating in the Ku-frequency band 11/14 GHz with an artificial satellite of the Earth in geostationary orbit are given. The dynamic range of signal power change at the input of the VSAT-based satellite ground receiver at different data rates is determined, which provides a given signal-to-noise ratio and bit error probability in the range of 10-7 – 10-4 for the required communication quality.
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Gutova, Svetlana Yrievna. "OVERTON-RESONANT SINGING BASIS OF COMPOSITOR LANGUAGE (OVERTONE-RESONANT BASIS OF COMPOSITOR LANGUAGE)." Chronos: social sciences 6, no. 3(23) (November 3, 2021): 4–11. http://dx.doi.org/10.52013/2712-9705-23-3-1.
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The article substantiates the embodiment of the traditional overtone intonational song beginning in the composer’s work. The application of the main acoustic features of an authentic timbre is described, such as compression, the presence of «specific resonances», reliance on the vocal position and inharmonic overtones. The main composer’s task is to create a piece of music that would imitate or reproduce the resonance characteristic of the folk singing tradition — the overtone. The research is based on the method of sound-acoustic measurement of an audio signal. The work was performed using the Reaper V4,581 audio editor software (Digital Audio Workstation) and a spectrograph built into the Reaper brand iZotop Ozon5 Advansed. This model of the spectrograph allows you to see the spectrogram of the investigated audio material in 3D format and color image, which more accurately reflects the measurements of the vibration frequency of the sound wave, and is also equipped with a broadband FFT analyzer. The scientific novelty of the research lies in the consideration of composer folklorism from the point of view of the timbre acoustic model of authentic singing, and the adaptation of expressive means is investigated not within the framework of the style and manner of the melodic presentation of the material of individual composers, but from the point of view of the timbre content of the folklore voice. The article shows how the influence of ethno-singing on composer’s creativity is revealed through the prism of authentic timbre and the given spectral examples.
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Newton, Nathan J. "When Analysts Speak, Do Auditors Listen?" AUDITING: A Journal of Practice & Theory 38, no. 1 (February 1, 2018): 221–45. http://dx.doi.org/10.2308/ajpt-52059.
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SUMMARY Prior studies examining the interactions of auditors and analysts have generally focused on how auditors influence analysts' forecasts or audit clients' behavior relative to those forecasts without considering how analysts might influence auditors. However, auditing standards encourage auditors to incorporate analyst-provided information into their risk assessment and audit planning. This study investigates whether auditors respond to a signal of potential misstatement risk derived from differences between auditors' earnings expectations and analysts' forecasts. Results indicate that auditors respond to this signal by charging higher fees and delaying the release of the audit report, which in combination suggest greater audit effort. Further, this signal reflects actual misstatement risk in the form of subsequent restatements, but audit effort mitigates this risk. Finally, auditors' response to analyst information is attenuated when forecast dispersion and forecast error suggest the signal lacks credibility. Overall, these findings suggest that auditors incorporate analyst-provided information into the audit process. JEL Classifications: M41; M42; M48.
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Chalapathi, M. M. Venkata, M. Rudra Kumar, Neeraj Sharma, and S. Shitharth. "Ensemble Learning by High-Dimensional Acoustic Features for Emotion Recognition from Speech Audio Signal." Security and Communication Networks 2022 (February 28, 2022): 1–10. http://dx.doi.org/10.1155/2022/8777026.
Повний текст джерелаАнотація:
In the recent past, handling the high dimensionality demonstrated in the auditory features of speech signals has been a primary focus for machine learning (ML-)based emotion recognition. The incorporation of high-dimensional characteristics in training datasets in the learning phase of ML models influences contemporary approaches to emotion prediction with significant false alerting. The curse of the excessive dimensionality of the training corpus is addressed in the majority of contemporary models. Modern models, on the other hand, place a greater emphasis on merging many classifiers, which can only increase emotion recognition accuracy even when the training corpus contains high-dimensional data points. “Ensemble Learning by High-Dimensional Acoustic Features (EL-HDAF)” is an innovative ensemble model that leverages the diversity assessment of feature values spanned over diversified classes to recommend the best features. Furthermore, the proposed technique employs a one-of-a-kind clustering process to limit the impact of high-dimensional feature values. The experimental inquiry evaluates and compares emotion forecasting using spoken audio data to current methods that use machine learning for emotion recognition. Fourfold cross-validation is used for performance analysis with the standard data corpus.
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Zgank, Andrej. "Bee Swarm Activity Acoustic Classification for an IoT-Based Farm Service." Sensors 20, no. 1 (December 19, 2019): 21. http://dx.doi.org/10.3390/s20010021.
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Beekeeping is one of the widespread and traditional fields in agriculture, where Internet of Things (IoT)-based solutions and machine learning approaches can ease and improve beehive management significantly. A particularly important activity is bee swarming. A beehive monitoring system can be applied for digital farming to alert the user via a service about the beginning of swarming, which requires a response. An IoT-based bee activity acoustic classification system is proposed in this paper. The audio data needed for acoustic training was collected from the Open Source Beehives Project. The input audio signal was converted into feature vectors, using the Mel-Frequency Cepstral Coefficients (with cepstral mean normalization) and Linear Predictive Coding. The influence of the acoustic background noise and denoising procedure was evaluated in an additional step. Different Hidden Markov Models’ and Gaussian Mixture Models’ topologies were developed for acoustic modeling, with the objective being to determine the most suitable one for the proposed IoT-based solution. The evaluation was carried out with a separate test set, in order to successfully classify sound between the normal and swarming conditions in a beehive. The evaluation results showed that good acoustic classification performance can be achieved with the proposed system.
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Wang, Chuyu, Lei Xie, Yuancan Lin, Wei Wang, Yingying Chen, Yanling Bu, Kai Zhang, and Sanglu Lu. "Thru-the-wall Eavesdropping on Loudspeakers via RFID by Capturing Sub-mm Level Vibration." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 5, no. 4 (December 27, 2021): 1–25. http://dx.doi.org/10.1145/3494975.
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The unprecedented success of speech recognition methods has stimulated the wide usage of intelligent audio systems, which provides new attack opportunities for stealing the user privacy through eavesdropping on the loudspeakers. Effective eavesdropping methods employ a high-speed camera, relying on LOS to measure object vibrations, or utilize WiFi MIMO antenna array, requiring to eavesdrop in quiet environments. In this paper, we explore the possibility of eavesdropping on the loudspeaker based on COTS RFID tags, which are prevalently deployed in many corners of our daily lives. We propose Tag-Bug that focuses on the human voice with complex frequency bands and performs the thru-the-wall eavesdropping on the loudspeaker by capturing sub-mm level vibration. Tag-Bug extracts sound characteristics through two means: (1) Vibration effect, where a tag directly vibrates caused by sounds; (2) Reflection effect, where a tag does not vibrate but senses the reflection signals from nearby vibrating objects. To amplify the influence of vibration signals, we design a new signal feature referred as Modulated Signal Difference (MSD) to reconstruct the sound from RF-signals. To improve the quality of the reconstructed sound for human voice recognition, we apply a Conditional Generative Adversarial Network (CGAN) to recover the full-frequency band from the partial-frequency band of the reconstructed sound. Extensive experiments on the USRP platform show that Tag-Bug can successfully capture the monotone sound when the loudness is larger than 60dB. Tag-Bug can efficiently recognize the numbers of human voice with 95.3%, 85.3% and 87.5% precision in the free-space eavesdropping, thru-the-brick-wall eavesdropping and thru-the-insulating-glass eavesdropping, respectively. Tag-Bug can also accurately recognize the letters with 87% precision in the free-space eavesdropping.
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Jung, Oliver. "Assessment of Conversational Speech Quality Inside Vehicles, Concerning Influences of Room Acoustics and Driving Noises." Acta Acustica united with Acustica 98, no. 3 (May 1, 2012): 461–74. http://dx.doi.org/10.3813/aaa.918530.
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This study considers the influences of room acoustics and driving noises in vehicle interiors on the subjectively perceived acoustical quality of conversations between passengers. A listening test with 25 participants was performed inside a laboratory to assess the impact of different vehicle interior transfer functions on the speech quality assessment in four predetermined dimensions. Idealized driving noises at three different vehicle speeds were presented simultaneously with speech samples to quantify the interferences of these noise conditions with varied signal-to-noise ratios. To minimize the influence of different human speakers, four talkers (two male and two female) were selected from commercially available audio books. The respective speech samples were adjusted in level and long-term average speech spectrum to the common values of conversational speech. The automatic reflex of raising one's voice in noisy environments, called “Lombard Effect” [1], was taken into account for an additional adjustment of speech levels while driving noises were present. A strong relationship between the speech-to-noise ratio and the test participants' evaluations was found. Thus, one can assume that the speech signals' attenuation or amplification caused by the different room acoustics of the tested vehicles play a more important role for a sufficient speech quality than the varied speech timbre or other parameters. Only at very high speech-to-noise ratios ( ≥ 20 dB with A-weighting), room-acoustical parameters such as IACC or the reverberation time are more determining for the speech quality appreciation than the speech's sound pressure level.
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Hennessy, Lachlan, and James Macnae. "Source-dependent bias of sferics in magnetotelluric responses." GEOPHYSICS 83, no. 3 (May 1, 2018): E161—E171. http://dx.doi.org/10.1190/geo2017-0434.1.
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The predominant signals of audio-frequency magnetotellurics (AMT) are called sferics, and they are generated by global lightning activity. When sferic signals are small or infrequent, measurement noise in electric and magnetic fields causes errors in estimated apparent resistivity and phase curves, leading to great model uncertainty. To reduce bias in apparent resistivity and phase, we use a global propagation model to link sferic signals in time series AMT data with commercially available lightning source information including strike time, location, and peak current. We then investigate relationships between lightning strike location, peak current, and the quality of the estimated apparent resistivity and phase curves using the bounded influence remote reference processing code. We use two empirical approaches to preprocessing time-series AMT data before estimation of apparent resistivity and phase: stitching and stacking (averaging). We find that for single-site AMT data, bias can be reduced by processing sferics from the closest and most powerful lightning strikes and omitting the lower amplitude signal-deficient segments in between. We hypothesized that bias can be further reduced by stacking sferics on the assumptions that lightning dipole moments are log-normally distributed whereas the superposed noise is normally distributed. Due to interference between dissimilar sferic waveforms, we tested a hybrid stitching-stacking approached based on clustering sferics using a wavelet-based waveform similarity algorithm. Our results indicate that the best approach to reduce bias was to stitch the closest and highest amplitude data.
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Fan, Qiaozhen. "The Application of Minority Music Style Recognition Based on Deep Convolution Loop Neural Network." Wireless Communications and Mobile Computing 2022 (March 29, 2022): 1–8. http://dx.doi.org/10.1155/2022/4556135.
Повний текст джерелаАнотація:
In recent years, with the development of Internet and digital audio technology, music information retrieval has gradually become a research hotspot. Due to the rise of deep learning and machine learning in recent years, as well as the rapid improvement of computer software and hardware performance, it has laid a good foundation for identifying different genres of music. Among them, the application of minority music style recognition is also an important research direction. At present, the application performance of minority music style recognition based on deep convolution loop neural network is poor. Because convolution loop neural networks (CNNs) have strong ability to capture information features, this paper uses CNN to extract various features from music signals and classify them. Firstly, the original music signal spectrum is separated into time characteristic harmonic component and frequency characteristic impact component by using the harmonic/percussive sound separation (HPSS) algorithm. Combined with the original spectra as the input of CNN, the network structure of CNN is designed, and the influence of different parameters in the network structure on the recognition rate is studied. Experiments on minority music data sets, compared with other scholars’ music recognition methods, it shows that this method can effectively improve the recognition of minority music styles using a single feature.
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Noland, Katy, and Mark Sandler. "Influences of Signal Processing, Tone Profiles, and Chord Progressions on a Model for Estimating the Musical Key from Audio." Computer Music Journal 33, no. 1 (March 2009): 42–56. http://dx.doi.org/10.1162/comj.2009.33.1.42.
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Hohm, Julian, Michael Döllinger, Christopher Bohr, Stefan Kniesburges, and Anke Ziethe. "Influence of F0 and Sequence Length of Audio and Electroglottographic Signals on Perturbation Measures for Voice Assessment." Journal of Voice 29, no. 4 (July 2015): 517.e11–517.e21. http://dx.doi.org/10.1016/j.jvoice.2014.10.001.
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Maldonado, Ivan, Alfredo Illanes, Marco Kalmar, Thomas Sühn, Axel Boese, and Michael Friebe. "Audio waves and its loss of energy in puncture needles." Current Directions in Biomedical Engineering 5, no. 1 (September 1, 2019): 21–24. http://dx.doi.org/10.1515/cdbme-2019-0006.
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AbstractThe location of a puncture needle’s tip and the resistance of tissue against puncture are crucial information for clinicians during a percutaneous procedure. The tip location and needle alignment can be observed by image guidance. Tactile information caused by tissue resistance to rupture, allow clinicians the perception of structural changes during puncture. Nevertheless, this sense is individual and subjective. To improve percutaneous procedures, the implementation of transducers to enhance or complement the senses offer objective feedback to the user. Known approaches are e.g. based on integrated force sensors. However, this is connected to higher device costs, sterilization and certification issues. A recent publication shows the implementation of an audio transducer clipped at the proximal end of the needle. This sensor is capable of acquiring emitted sounds of the distal tiptissue interaction that are transmitted over the needle structure. The interpretation of the measured audio signals is highly depended on the transmission over the needle, the tissue and, the penetration depth. To evaluate the influence of these parameters, this work implements a simplified experimental setup in a controlled environment with a minimum of noise and without micro tremors induced by clinician’s hands. A steel rod simulating a needle is inserted into pork meat of different thickness. A controlled impact covering the needle’s tip mimics tissue contact. The resulting signals are recorded and analyzed for better understanding of the system.
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Siegert, Ingo, Vered Silber-Varod, Nehoray Carmi, and Pawel Kamocki. "Personal data protection and academia: GDPR issues and multi-modal data-collections "in the wild"." Online Journal of Applied Knowledge Management 8, no. 1 (June 14, 2020): 16–31. http://dx.doi.org/10.36965/ojakm.2020.8(1)16-31.
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The European Union (EU) General Data Protection Regulations (GDPR) has a direct impact on research activities, as it raises the awareness of personal rights not only among the scientists but also among the data-subjects scientists process information from. This paper presents the dilemma related to the privacy of audio and video data, compliance with the EU GDPR, and techniques to anonymize and pseudonymize such data. We further discuss issues of “in the wild” personal data collection by focusing on multi-modal collections, mainly of audio, video via these channels. Throughout this paper we define relevant core issues and highlight two challenges of “in the wild” data collection: Internet crawling and public data collecting. In the last section, some exemplary use cases are demonstrating the raised issues, illuminating how GDPR affects the collection of publicly available data; how privacy concerns influence participant behavior, and which de-anonymization levels can be reached with what kind of data. The key point we present is that the identity of the participants is revealed in the voice or video signal, while the latter is at the same time the object of the research. One implication is that the research community has to actively disconnect the data from the personal information on the participants. Hence the importance of a process of anonymity or omission of data for research activity. This entail the development of an infrastructure for data access control to enable data sharing among researchers
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Andriyanov, N. A. "RECOGNITION OF RADIO EXCHANGE VOICE MESSAGES IN AVIATION BASED ON CORRELATION ANALYSIS." Izvestiya of Samara Scientific Center of the Russian Academy of Sciences 23, no. 1 (2021): 91–96. http://dx.doi.org/10.37313/1990-5378-2021-23-1-91-96.
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The paper considers the problem of speech messages recognition in phraseological radio exchange for tasks of civil aviation. The introduction substantiates the relevance of this problem. The following are research methods based on correlation analysis. Finally, a description of the experiment and the results of the recognition algorithms based on correlation analysis are given. Various variants were recorded for five speech messages and spectral representations of such signals were constructed. Spectral transform can be obtained either using specialized software or based on the Fourier transform of the signal in the time domain. To obtain a more universal reference signal and eliminate the influence of interference, the spectral components of the same speech message recorded several times were averaged. In fact, three spectra of the same speech message were used for averaging. This spectrum averaging over three training components provided a reference sample of phrases or patterns for each phrase, and reduced the influence of additive white Gaussian noise in the reference. Later, on the basis of correlation analysis, the connections between test phrases and all patterns were calculated. On the basis of these connections, a correlation matrix of reference phrases is built. Research has shown that phrases spoken by one person were highly correlated. The analysis showed that the choice of the class (the content of the speech message) when solving the recognition problem corresponding to the value of the correlation coefficient closest to one provides over 90% of correct recognitions on a test sample containing a total of 100 phrases, 20 for each phrase. It should be noted that, when recording test messages, an additive white Gaussian noise was additionally present as a background, reproduced by another audio device. In the case of information analysis without artificially generated noise, the probability of correct recognition for a test sample of 100 phrases, 20 for each phrase, is 100% when using correlation analysis.
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Polyanina, Alla. "Media Noise: the problem of hygienic rationing and personal well-being." E3S Web of Conferences 291 (2021): 05004. http://dx.doi.org/10.1051/e3sconf/202129105004.
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The article raises the problem of hygienic rationing of a special type of noise, the nature of which stems from the sources of public information – the mass media. The author develops a new concept of comprehending this type of noise – the concept of Media Noise. Such noise is associated with the special nature of its perception and consumption in the background mode that acts as a risk factor for human health and well-being. The author points out such specific characteristics of the media noise that relate it to certain risk factors, namely: hyperstimulation of the auditory analyzer and the inability to control its implementation (work), that is, the compulsion of perception. This second key feature of the media noise is similar to mental violence, if the audio signal is used by an external subject, for example, in public places or transport, and its broadcasting excludes the possibility for the perceiving subject to influence upon the source of noise (a screen or a player).
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Asthana, Sharad C., and Jeff P. Boone. "Abnormal Audit Fee and Audit Quality." AUDITING: A Journal of Practice & Theory 31, no. 3 (August 1, 2012): 1–22. http://dx.doi.org/10.2308/ajpt-10294.
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SUMMARY This study tests the hypotheses that below-normal audit fees signal important nuances in the balance of bargaining power between the auditor and the client, and that such power may ultimately influence audit quality. We find that audit quality, proxied by absolute discretionary accruals and meeting or beating analysts' earnings forecasts, declines as negative abnormal audit fees increase in magnitude, with the effect amplified as proxies for client bargaining power increase. We find that this effect is dampened in years following the Sarbanes-Oxley Act (SOX), suggesting that SOX was effective in enhancing auditor independence.
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Oren, Liran. "Effect of nasendoscopy procedure on acoustic features of voice and speech." Journal of the Acoustical Society of America 151, no. 4 (April 2022): A45. http://dx.doi.org/10.1121/10.0010607.
Повний текст джерелаАнотація:
Nasendoscopy procedure enables direct visualization of voice and speech anatomy. The procedure passes a flexible scope transnasally to observe velopharyngeal mechanism or the larynx during speech and phonation. This imaging technique is commonly used simultaneously with audio recordings. Studies have identified important statistically-significant relationships between imaging-based and acoustic measures related to voice and speech quality. However, the effect of the nasendoscopy procedure itself on specific acoustic features is rarely being considered. Nasendoscopy is likely to cause some speakers to deviate from their typical vocal function by inducing stress and tension during recordings. Furthermore, the flexible nasendoscope can also change the sound and airflow behavior inside the vocal tract. The current study attempts to quantify how nasendoscopy influences acoustic features using a physical model based on a child's vocal tractduring a sibilant sound. An electrolarynx was used to provide a constant sound source with the input airflow to the model. Audio recordings were captured while retracting the nasendoscope from the level of the hypopharynx. Results show that compared to the same data taken without nasendoscopy, the scope can change measures of signal-to-noise and cepstral-peak-prominence by 15% and 7%, respectively. The nasendoscope had a minimal effect (<3%) on the SPL measure.
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Lowenberg, Richard. "Creative Works Exploring Our Information Ecosystem: 1970–1979." Leonardo 53, no. 5 (October 2020): 571–77. http://dx.doi.org/10.1162/leon_a_01909.
Повний текст джерелаАнотація:
In the 1970s, Richard Lowenberg embarked upon the first in a series of experimental artworks that were conceptualized as part of a lifelong body of works addressing aspects of our information environment as ecosystem. Creative works during this period were influenced by information theory and cybernetics, the electromagnetic spectrum, the nature of signal, feedback, sensing-communicating, language and emerging media technologies. Artistic milestones included video-audio synthesis, NASA arts collaborations, interactions with Koko the gorilla, creation of sequences for the Secret Life of Plants film and EEG-EMGEKG biotelemetric performances (“Bio-Dis-Plays”). Real life offered a number of unexpected opportunities and distractions that enriched this work and helped set a course for development and realization of subsequent projects along an intended ecocultural path.
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Bańburski, Łukasz. "Telewizyjne kanały tematyczne w Polsce w kontekście przemian technologicznych i dominacji nowych mediów." Załącznik Kulturoznawczy, no. 4 (2017): 177–200. http://dx.doi.org/10.21697/zk.2017.4.08.
Повний текст джерелаАнотація:
In the article, a broad topic of thematic channels on the Polish market has been taken up. Thematic channels, increasingly popular and obtaining more and more media coverage, fit well into the landscape of television, gaining a large audience and changing the way television is perceived by Poles. The author proposes various ways of categorizing thematic channels, because of: the type of concessions, thematic segments, television signal sources, media groups, financing methods. He provides information on viewership of the station. He also focuses on alternative (to traditional television) ways of receiving audio content (videotapes, DVD players, home video systems, smart TVs, hybrid TVs, on-demand services), and defines how they have influenced the shape of contemporary television as well as the development of thematic channels.
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Ivančová, Lena. "K Intonologickej Charakteristike Slabiky V Slovenčine." Journal of Linguistics/Jazykovedný casopis 69, no. 2 (December 1, 2018): 125–39. http://dx.doi.org/10.2478/jazcas-2019-0001.
Повний текст джерелаАнотація:
Abstract The paper analyses the intonation of syllables in broadcasted communication utterances (analyzing audio samples from radio programs Rádiožurnál and Literárna revue Rádia Slovensko) from theoretical point of view, while building upon the outcomes of the experimental phonetic research. Duration of the individual segments, intensity of sonantic cores including intensity of syllables and basic frequency F0 were analysed. Role of the analysed parameters in relation to the sonic formation of the text can be seen in exact graphs, which are cross-referenced by the measured values. The analysis has shown that an intonation differentiation of text-forming features in the broadcasted communication utterances is significantly influenced by tonal modulation (melody). Variation potential of time modulation is limited by faster pace of broadcasted texts. The strength modulation is demonstrably limited by signal standardization in radio broadcasting.
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Bastine, Amy, Thushara D. Abhayapala, and Jihui (Aimee) Zhang. "Time-frequency-dependent directional analysis of room reflections using eigenbeam processing and von Mises–Fisher clustering." Journal of the Acoustical Society of America 151, no. 5 (May 2022): 2916–30. http://dx.doi.org/10.1121/10.0010380.
Повний текст джерелаАнотація:
The knowledge of frequency-dependent spatiotemporal features of the reflected soundfield is essential in optimizing the perception quality of spatial audio applications. For this purpose, we need a reliable room acoustic analyzer that can conceive the spatial variations in a decaying reflected soundfield according to the frequency-dependent surface properties and source directivity. This paper introduces a time-frequency-dependent angular reflection power distribution model represented by a von Mises–Fisher (vMF) mixture function to facilitate manifold analysis of a reverberant soundfield. The proposed approach utilizes the spatial correlation of higher-order eigenbeams to deduce the directional reflection power vectors, which are then synthesized into a vMF mixture model. The experimental study demonstrates the directional power variations of early reflections and late reverberations across different frequencies. This work also introduces a measure called the directivity time-span to quantify the duration of anisotropic reflections before it decays into a totally diffused field. We validate the subband performance by comparing it with the eigenbeam multiple signal classification method. The results prove the influence of source position, source directivity, and room environment in the distribution of reflection power, whereas the directivity time-span behaves independent of the source positions.
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Wulandari, Ketut Memi, and Ketut Muliartha. "Good Corporate Governance sebagai Pemoderasi Pengaruh Financial Distress pada Opini Audit Going Concern." E-Jurnal Akuntansi 28, no. 2 (August 10, 2019): 1170. http://dx.doi.org/10.24843/eja.2019.v28.i02.p15.
Повний текст джерелаАнотація:
This research uses manufacturing companies listed on the Indonesia Stock Exchange as research’s objects. The number of samples are 210 with using the purposive sampling method. Data collection is done using documentation. The data analysis technique used is Moderated Regression Analysis. Based on the results of the analysis, it was found that the application of good corporate governance to the company is able to weaken the influence of financial distress on the going concern audit opinion. The implications of the results of the study support the signal theory seen in the results of the financial distress which tends to signal the auditor to give a going-concern audit opinion. The results of the study also support agency theory where the tendency for information asymmetry between agents and principals, especially for companies in experience financial distress.Keywords: Financial distress, good corporate governance, going-concern audit opinion.
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Szydłowski, Tomasz, Krzysztof Surmiński, and Damian Batory. "Drivers’ Psychomotor Reaction Times Tested with a Test Station Method." Applied Sciences 11, no. 5 (March 9, 2021): 2431. http://dx.doi.org/10.3390/app11052431.
Повний текст джерелаАнотація:
The article presents the standard method of the evaluation of car drivers’ psychomotor reaction times. A characteristic feature of this method is the ability to conduct tests using real vehicles equipped with mobile measuring apparatus. Measurements are carried out on people whose task is to initiate specific maneuvers (such as: a braking or turning maneuver, a combined braking and turning maneuver, as well as e.g., the use of an audio signal) in response to external stimuli coming from different directions. The sources of the stimuli are light signals emitted by variable message signs placed around the vehicle. The developed control and measurement equipment allows us to realize various and complex test scenarios. It generates stimulus sequences, assesses the correctness of the driver’s response and measures its time. This method allows us to obtain sets of results from tests carried out under different conditions and variable test durations. The possibility of testing a large number of participants in a relatively short time and in repetitive conditions allows for reliable statistical inference. The paper presents examples of research results obtained on the basis of few thousand tests carried out on a large group of respondents. The registered data was statistically processed and referred to the literature. A high degree of correlation between the analyzed results and the literature reports proves that the presented method may be a source of data for the analysis of phenomena related to the time of the driver’s response, especially the influence of various factors affecting its values.
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Solimine, Jaclyn, Christopher Niezrecki, and Murat Inalpolat. "An experimental investigation into passive acoustic damage detection for structural health monitoring of wind turbine blades." Structural Health Monitoring 19, no. 6 (January 3, 2020): 1711–25. http://dx.doi.org/10.1177/1475921719895588.
Повний текст джерелаАнотація:
This article details the implementation of a novel passive structural health monitoring approach for damage detection in wind turbine blades using airborne sound. The approach utilizes blade-internal microphones to detect trends, shifts, or spikes in the sound pressure level of the blade cavity using a limited network of internally distributed airborne acoustic sensors, naturally occurring passive system excitation, and periodic measurement windows. A test campaign was performed on a utility-scale wind turbine blade undergoing fatigue testing to demonstrate the ability of the method for structural health monitoring applications. The preliminary audio signal processing steps used in the study, which were heavily influenced by those methods commonly utilized in speech-processing applications, are discussed in detail. Principal component analysis and K-means clustering are applied to the feature-space representation of the data set to identify any outliers (synonymous with deviations from the normal operation of the wind turbine blade) in the measurements. The performance of the system is evaluated based on its ability to detect those structural events in the blade that are identified by making manual observations of the measurements. The signal processing methods proposed within the article are shown to be successful in detecting structural and acoustic aberrations experienced by a full-scale wind turbine blade undergoing fatigue testing. Following the assessment of the data, recommendations are given to address the future development of the approach in terms of physical limitations, signal processing techniques, and machine learning options.
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Abdurrachman, Abdurrachman, Rizky Amalia, and Bryan Givan. "ANALISIS PENGARUH PROFITABILITAS DAN LIKUIDITAS TERHADAP OPINI AUDIT GOING CONCERN." Progress: Jurnal Pendidikan, Akuntansi dan Keuangan 4, no. 2 (August 24, 2021): 129–35. http://dx.doi.org/10.47080/progress.v4i2.1333.
Повний текст джерелаАнотація:
Companies that receive a going concern audit opinion show events and conditions that would cause the auditor to doubt about the going concern of the company. This opinion can be used as an initial signal for users of financial statements to avoid mistakes when making a decision. Regarding the factors that influence going-concern audit opinion, many previous studies have been carried out. However, it has inconsistencies in the results of the study. Thus, the research aims to carry out retesting related "factors that influence going concern audit opinion". The variables tested include Profitability and Liquidity. The research sample uses manufactur companies in the consumer goods industry which were listed on the Indonesian Stock Exchange for the period 2018-2019. The sampling technique was purposive sampling, which obtained 102 companies’ data that matched the criteria. Logistic regression analysis was used to test the hypothesis of this study. Hypothesis testing results that partially the profitability and liquidity variables have no effect on going-concern audit opinion.