Статті в журналах з теми "Mel spectrogram analysis"
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Lambamo, Wondimu, Ramasamy Srinivasagan, and Worku Jifara. "Analyzing Noise Robustness of Cochleogram and Mel Spectrogram Features in Deep Learning Based Speaker Recognition." Applied Sciences 13, no. 1 (December 31, 2022): 569. http://dx.doi.org/10.3390/app13010569.
Повний текст джерелаLiao, Ying. "Analysis of Rehabilitation Occupational Therapy Techniques Based on Instrumental Music Chinese Tonal Language Spectrogram Analysis." Occupational Therapy International 2022 (October 3, 2022): 1–12. http://dx.doi.org/10.1155/2022/1064441.
Повний текст джерелаByeon, Yeong-Hyeon, and Keun-Chang Kwak. "Pre-Configured Deep Convolutional Neural Networks with Various Time-Frequency Representations for Biometrics from ECG Signals." Applied Sciences 9, no. 22 (November 10, 2019): 4810. http://dx.doi.org/10.3390/app9224810.
Повний текст джерелаReddy, A. Pramod, and Vijayarajan V. "Fusion Based AER System Using Deep Learning Approach for Amplitude and Frequency Analysis." ACM Transactions on Asian and Low-Resource Language Information Processing 21, no. 3 (May 31, 2022): 1–19. http://dx.doi.org/10.1145/3488369.
Повний текст джерелаYu, Yeonguk, and Yoon-Joong Kim. "Attention-LSTM-Attention Model for Speech Emotion Recognition and Analysis of IEMOCAP Database." Electronics 9, no. 5 (April 26, 2020): 713. http://dx.doi.org/10.3390/electronics9050713.
Повний текст джерелаBous, Frederik, and Axel Roebel. "A Bottleneck Auto-Encoder for F0 Transformations on Speech and Singing Voice." Information 13, no. 3 (February 23, 2022): 102. http://dx.doi.org/10.3390/info13030102.
Повний текст джерелаRajan, Rajeev, and Sreejith Sivan. "Raga Recognition in Indian Carnatic Music Using Convolutional Neural Networks." WSEAS TRANSACTIONS ON ACOUSTICS AND MUSIC 9 (May 7, 2022): 5–10. http://dx.doi.org/10.37394/232019.2022.9.2.
Повний текст джерелаPapadimitriou, Ioannis, Anastasios Vafeiadis, Antonios Lalas, Konstantinos Votis, and Dimitrios Tzovaras. "Audio-Based Event Detection at Different SNR Settings Using Two-Dimensional Spectrogram Magnitude Representations." Electronics 9, no. 10 (September 29, 2020): 1593. http://dx.doi.org/10.3390/electronics9101593.
Повний текст джерелаYazgaç, Bilgi Görkem, and Mürvet Kırcı. "Fractional-Order Calculus-Based Data Augmentation Methods for Environmental Sound Classification with Deep Learning." Fractal and Fractional 6, no. 10 (September 29, 2022): 555. http://dx.doi.org/10.3390/fractalfract6100555.
Повний текст джерелаBarile, C., C. Casavola, G. Pappalettera, and P. K. Vimalathithan. "Sound of a Composite Failure: An Acoustic Emission Investigation." IOP Conference Series: Materials Science and Engineering 1214, no. 1 (January 1, 2022): 012006. http://dx.doi.org/10.1088/1757-899x/1214/1/012006.
Повний текст джерелаChen, Wei, and Guobin Wu. "A Multimodal Convolutional Neural Network Model for the Analysis of Music Genre on Children’s Emotions Influence Intelligence." Computational Intelligence and Neuroscience 2022 (August 29, 2022): 1–11. http://dx.doi.org/10.1155/2022/5611456.
Повний текст джерелаHong, Joonki, Hai Tran, Jinhwan Jeong, Hyeryung Jang, In-Young Yoon, Jung Kyung Hong, and Jeong-Whun Kim. "0348 Sleep Staging Using End-to-End Deep Learning Model Based on Nocturnal Sound for Smartphones." Sleep 45, Supplement_1 (May 25, 2022): A156—A157. http://dx.doi.org/10.1093/sleep/zsac079.345.
Повний текст джерелаHajarolasvadi, Noushin, and Hasan Demirel. "3D CNN-Based Speech Emotion Recognition Using K-Means Clustering and Spectrograms." Entropy 21, no. 5 (May 8, 2019): 479. http://dx.doi.org/10.3390/e21050479.
Повний текст джерелаKim, Daeyeol, Tegg Taekyong Sung, Soo Young Cho, Gyunghak Lee, and Chae Bong Sohn. "A Single Predominant Instrument Recognition of Polyphonic Music Using CNN-based Timbre Analysis." International Journal of Engineering & Technology 7, no. 3.34 (September 1, 2018): 590. http://dx.doi.org/10.14419/ijet.v7i3.34.19388.
Повний текст джерелаKim, Heejung, Youngshin Cho, Sunghee Lee, and Chaehyeon Kang. "MULTIMODAL AFFECTIVE ANALYSIS OF FACIAL AND VOCAL EXPRESSIVITY USING SMARTPHONE AND DEEP LEARNING ANALYSIS." Innovation in Aging 6, Supplement_1 (November 1, 2022): 593–94. http://dx.doi.org/10.1093/geroni/igac059.2221.
Повний текст джерелаMaskeliūnas, Rytis, Audrius Kulikajevas, Robertas Damaševičius, Kipras Pribuišis, Nora Ulozaitė-Stanienė, and Virgilijus Uloza. "Lightweight Deep Learning Model for Assessment of Substitution Voicing and Speech after Laryngeal Carcinoma Surgery." Cancers 14, no. 10 (May 11, 2022): 2366. http://dx.doi.org/10.3390/cancers14102366.
Повний текст джерелаDzulfikar, Helmy, Sisdarmanto Adinandra, and Erika Ramadhani. "The Comparison of Audio Analysis Using Audio Forensic Technique and Mel Frequency Cepstral Coefficient Method (MFCC) as the Requirement of Digital Evidence." Jurnal Online Informatika 6, no. 2 (December 26, 2021): 145. http://dx.doi.org/10.15575/join.v6i2.702.
Повний текст джерелаKumari, Neha. "Music Genre Classification for Indian Music Genres." International Journal for Research in Applied Science and Engineering Technology 9, no. 8 (August 31, 2021): 1756–62. http://dx.doi.org/10.22214/ijraset.2021.37669.
Повний текст джерелаKim, Jeonghyeon, Jonghoek Kim, and Hyuntai Kim. "A Study on Gear Defect Detection via Frequency Analysis Based on DNN." Machines 10, no. 8 (August 5, 2022): 659. http://dx.doi.org/10.3390/machines10080659.
Повний текст джерелаHe, Jinzheng, Zhou Zhao, Yi Ren, Jinglin Liu, Baoxing Huai, and Nicholas Yuan. "Flow-Based Unconstrained Lip to Speech Generation." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 1 (June 28, 2022): 843–51. http://dx.doi.org/10.1609/aaai.v36i1.19966.
Повний текст джерелаUtebayeva, Dana, Lyazzat Ilipbayeva, and Eric T. Matson. "Practical Study of Recurrent Neural Networks for Efficient Real-Time Drone Sound Detection: A Review." Drones 7, no. 1 (December 30, 2022): 26. http://dx.doi.org/10.3390/drones7010026.
Повний текст джерелаde Benito-Gorrón, Diego, Daniel Ramos, and Doroteo T. Toledano. "An Analysis of Sound Event Detection under Acoustic Degradation Using Multi-Resolution Systems." Applied Sciences 11, no. 23 (December 6, 2021): 11561. http://dx.doi.org/10.3390/app112311561.
Повний текст джерелаKim, Jaehoon, Jeongkyu Oh, and Tae-Young Heo. "Acoustic Scene Classification and Visualization of Beehive Sounds Using Machine Learning Algorithms and Grad-CAM." Mathematical Problems in Engineering 2021 (May 24, 2021): 1–13. http://dx.doi.org/10.1155/2021/5594498.
Повний текст джерелаZakariah, Mohammed, Reshma B, Yousef Ajmi Alothaibi, Yanhui Guo, Kiet Tran-Trung, and Mohammad Mamun Elahi. "An Analytical Study of Speech Pathology Detection Based on MFCC and Deep Neural Networks." Computational and Mathematical Methods in Medicine 2022 (April 4, 2022): 1–15. http://dx.doi.org/10.1155/2022/7814952.
Повний текст джерелаSrivastava, Arpan, Sonakshi Jain, Ryan Miranda, Shruti Patil, Sharnil Pandya, and Ketan Kotecha. "Deep learning based respiratory sound analysis for detection of chronic obstructive pulmonary disease." PeerJ Computer Science 7 (February 11, 2021): e369. http://dx.doi.org/10.7717/peerj-cs.369.
Повний текст джерелаAggarwal, Apeksha, Akshat Srivastava, Ajay Agarwal, Nidhi Chahal, Dilbag Singh, Abeer Ali Alnuaim, Aseel Alhadlaq, and Heung-No Lee. "Two-Way Feature Extraction for Speech Emotion Recognition Using Deep Learning." Sensors 22, no. 6 (March 19, 2022): 2378. http://dx.doi.org/10.3390/s22062378.
Повний текст джерелаUloza, Virgilijus, Rytis Maskeliunas, Kipras Pribuisis, Saulius Vaitkus, Audrius Kulikajevas, and Robertas Damasevicius. "An Artificial Intelligence-Based Algorithm for the Assessment of Substitution Voicing." Applied Sciences 12, no. 19 (September 28, 2022): 9748. http://dx.doi.org/10.3390/app12199748.
Повний текст джерелаRao, Sunil, Vivek Narayanaswamy, Michael Esposito, Jayaraman J. Thiagarajan, and Andreas Spanias. "COVID-19 detection using cough sound analysis and deep learning algorithms." Intelligent Decision Technologies 15, no. 4 (January 10, 2022): 655–65. http://dx.doi.org/10.3233/idt-210206.
Повний текст джерелаAn, Ji-Hee, Na-Kyoung Koo, Ju-Hye Son, Hye-Min Joo, and Seungdo Jeong. "Development on Deaf Support Application Based on Daily Sound Classification Using Image-based Deep Learning." JOIV : International Journal on Informatics Visualization 6, no. 1-2 (May 31, 2022): 250. http://dx.doi.org/10.30630/joiv.6.1-2.936.
Повний текст джерелаIlarionov, Oleg, Anton Astakhov, Anna Krasovska, and Iryna Domanetska. "Intelligent module for recognizing emotions by voice." Advanced Information Technology, no. 1 (1) (2021): 46–52. http://dx.doi.org/10.17721/ait.2021.1.06.
Повний текст джерелаAkinpelu, Samson, and Serestina Viriri. "Robust Feature Selection-Based Speech Emotion Classification Using Deep Transfer Learning." Applied Sciences 12, no. 16 (August 18, 2022): 8265. http://dx.doi.org/10.3390/app12168265.
Повний текст джерелаLee, Seungwoo, Iksu Seo, Jongwon Seok, Yunsu Kim, and Dong Seog Han. "Active Sonar Target Classification with Power-Normalized Cepstral Coefficients and Convolutional Neural Network." Applied Sciences 10, no. 23 (November 26, 2020): 8450. http://dx.doi.org/10.3390/app10238450.
Повний текст джерелаĆirić, Dejan G., Zoran H. Perić, Nikola J. Vučić, and Miljan P. Miletić. "Analysis of Industrial Product Sound by Applying Image Similarity Measures." Mathematics 11, no. 3 (January 17, 2023): 498. http://dx.doi.org/10.3390/math11030498.
Повний текст джерелаSHIRAISHI, Toshihiko, and Tomoki DOURA. "Blind source separation by multilayer neural network classifiers for spectrogram analysis." Mechanical Engineering Journal 6, no. 6 (2019): 18–00527. http://dx.doi.org/10.1299/mej.18-00527.
Повний текст джерелаDumitrescu, Cătălin, Marius Minea, Ilona Mădălina Costea, Ionut Cosmin Chiva, and Augustin Semenescu. "Development of an Acoustic System for UAV Detection." Sensors 20, no. 17 (August 28, 2020): 4870. http://dx.doi.org/10.3390/s20174870.
Повний текст джерелаBayram, Barış, and Gökhan İnce. "An Incremental Class-Learning Approach with Acoustic Novelty Detection for Acoustic Event Recognition." Sensors 21, no. 19 (October 5, 2021): 6622. http://dx.doi.org/10.3390/s21196622.
Повний текст джерелаDalal, Sarang S., Johanna M. Zumer, Adrian G. Guggisberg, Michael Trumpis, Daniel D. E. Wong, Kensuke Sekihara, and Srikantan S. Nagarajan. "MEG/EEG Source Reconstruction, Statistical Evaluation, and Visualization with NUTMEG." Computational Intelligence and Neuroscience 2011 (2011): 1–17. http://dx.doi.org/10.1155/2011/758973.
Повний текст джерелаCiborowski, Tomasz, Szymon Reginis, Dawid Weber, Adam Kurowski, and Bozena Kostek. "Classifying Emotions in Film Music—A Deep Learning Approach." Electronics 10, no. 23 (November 27, 2021): 2955. http://dx.doi.org/10.3390/electronics10232955.
Повний текст джерелаSalian, Beenaa, Omkar Narvade, Rujuta Tambewagh, and Smita Bharne. "Speech Emotion Recognition using Time Distributed CNN and LSTM." ITM Web of Conferences 40 (2021): 03006. http://dx.doi.org/10.1051/itmconf/20214003006.
Повний текст джерелаKostek, Bozena. "Analysis-by-synthesis paradigm evolved into a new concept." Journal of the Acoustical Society of America 152, no. 4 (October 2022): A178. http://dx.doi.org/10.1121/10.0015955.
Повний текст джерелаXu, Xiaona, Li Yang, Yue Zhao, and Hui Wang. "End-to-End Speech Synthesis for Tibetan Multidialect." Complexity 2021 (January 25, 2021): 1–8. http://dx.doi.org/10.1155/2021/6682871.
Повний текст джерелаZhang, Lilun, Dezhi Wang, Changchun Bao, Yongxian Wang, and Kele Xu. "Large-Scale Whale-Call Classification by Transfer Learning on Multi-Scale Waveforms and Time-Frequency Features." Applied Sciences 9, no. 5 (March 12, 2019): 1020. http://dx.doi.org/10.3390/app9051020.
Повний текст джерелаGourishetti, Saichand, David Johnson, Sara Werner, András Kátai, and Peter Holstein. "Partial discharge monitoring using deep neural networks with acoustic emission." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no. 3 (August 1, 2021): 3312–23. http://dx.doi.org/10.3397/in-2021-2373.
Повний текст джерелаWitte, H., and M. Wacker. "Time-frequency Techniques in Biomedical Signal Analysis." Methods of Information in Medicine 52, no. 04 (2013): 279–96. http://dx.doi.org/10.3414/me12-01-0083.
Повний текст джерелаOstler, Daniel, Matthias Seibold, Jonas Fuchtmann, Nicole Samm, Hubertus Feussner, Dirk Wilhelm, and Nassir Navab. "Acoustic signal analysis of instrument–tissue interaction for minimally invasive interventions." International Journal of Computer Assisted Radiology and Surgery 15, no. 5 (April 22, 2020): 771–79. http://dx.doi.org/10.1007/s11548-020-02146-7.
Повний текст джерела"Spoken Language Identification using CNN with Log Mel Spectrogram Features in Indian Context." International Journal of Advanced Trends in Computer Science and Engineering 11, no. 6 (December 9, 2022): 273–79. http://dx.doi.org/10.30534/ijatcse/2022/071162022.
Повний текст джерела"Music Genre Classification using Spectral Analysis Techniques With Hybrid Convolution-Recurrent Neural Network." International Journal of Innovative Technology and Exploring Engineering 9, no. 1 (November 10, 2019): 149–54. http://dx.doi.org/10.35940/ijitee.a3956.119119.
Повний текст джерелаSaishu, Yuki, Amir Hossein Poorjam, and Mads Græsbøll Christensen. "A CNN-based approach to identification of degradations in speech signals." EURASIP Journal on Audio, Speech, and Music Processing 2021, no. 1 (February 5, 2021). http://dx.doi.org/10.1186/s13636-021-00198-4.
Повний текст джерелаSukumaran, Poornima, and Kousalya Govardhanan. "Towards voice based prediction and analysis of emotions in ASD children." Journal of Intelligent & Fuzzy Systems, March 22, 2021, 1–10. http://dx.doi.org/10.3233/jifs-189854.
Повний текст джерелаReghunath, Lekshmi Chandrika, and Rajeev Rajan. "Transformer-based ensemble method for multiple predominant instruments recognition in polyphonic music." EURASIP Journal on Audio, Speech, and Music Processing 2022, no. 1 (May 16, 2022). http://dx.doi.org/10.1186/s13636-022-00245-8.
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