Journal articles: 'Speech intelligibility prediction'

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Bradley, J. S. "Speech intelligibility prediction in rooms." Journal of the Acoustical Society of America 77, S1 (April 1985): S88. http://dx.doi.org/10.1121/1.2022570.

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Tamjis, Mohd Ridzwan, Muhammad Naufal Mansor, Ahmad Kadri Junoh, Amran Ahmed, Wan Suhana Wan Daud, and Azrini Idris. "Heterogeneous Speech Prediction Using LDA Classifiers." Advanced Materials Research 1016 (August 2014): 267–72. http://dx.doi.org/10.4028/www.scientific.net/amr.1016.267.

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Classroom speech intelligibility has become one of the main concerns in schools and other learning institutions development nowadays. This is because the qualities of student’s perceptions towards teacher are essentials in learning development. Measures have been introduced by the acoustical association to tackle the speech intelligibility problems in the classroom such as room renovations. Room’s acoustics standards have been introduced in several countries but still the questions on whether the standards fits on every classroom in different countries are still arise. Studies have also shown that most of the researches that have been conducted were only focusing on the conventional type classroom which depends only on the teacher’s vocal power. This paper will formulate the measurement protocol on measuring the speech intelligibility in the sound reinforced (multiple speaker) classroom. Finally it was found that the speech intelligibility in the sound reinforced classroom is better than the conventional classroom by using Linear Discriminant Analysis.

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van Schoonhoven, Jelmer, Koenraad S. Rhebergen, and Wouter A. Dreschler. "A context-based approach to predict speech intelligibility in interrupted noise: Model design." Journal of the Acoustical Society of America 151, no. 2 (February 2022): 1404–15. http://dx.doi.org/10.1121/10.0009617.

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The Extended Speech Transmission Index (ESTI) by van Schoonhoven et al. [(2019). J. Acoust. Soc. Am. 145, 1178–1194] was used successfully to predict intelligibility of sentences in fluctuating background noise. However, prediction accuracy was poor when the modulation frequency of the masker was low (<8 Hz). In the current paper, the ESTI was calculated per phoneme to estimate phoneme intelligibility. In the next step, the ESTI model was combined with one of two context models {Boothroyd and Nittrouer, [(1988). J. Acoust. Soc. Am. 84, 101–114]; Bronkhorst et al., [(1993). J. Acoust. Soc. Am. 93, 499–509} in order to improve model predictions. This approach was validated using interrupted speech data, after which it was used to predict speech intelligibility of words in interrupted noise. Model predictions improved using this new method, especially for maskers with interruption rates below 5 Hz. Calculating the ESTI at phoneme level combined with a context model is therefore a viable option to improve prediction accuracy.

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Marshall, L. Gerald. "Speech intelligibility prediction from calculated C50 values." Journal of the Acoustical Society of America 98, no. 5 (November 1995): 2845–47. http://dx.doi.org/10.1121/1.413184.

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Jensen, Jesper, and Cees H. Taal. "Speech Intelligibility Prediction Based on Mutual Information." IEEE/ACM Transactions on Audio, Speech, and Language Processing 22, no. 2 (February 2014): 430–40. http://dx.doi.org/10.1109/taslp.2013.2295914.

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Yamamoto, Katsuhiko, Toshio Irino, Toshie Matsui, Shoko Araki, Keisuke Kinoshita, and Tomohiro Nakatani. "Analysis of acoustic features for speech intelligibility prediction models analysis of acoustic features for speech intelligibility prediction models." Journal of the Acoustical Society of America 140, no. 4 (October 2016): 3114. http://dx.doi.org/10.1121/1.4969744.

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Croce, Paolo, Francesco Leccese, Giacomo Salvadori, and Umberto Berardi. "Proposal of a Simplified Tool for Early Acoustics Design Stage of Classrooms in Compliance with Speech Intelligibility Thresholds." Energies 16, no. 2 (January 10, 2023): 813. http://dx.doi.org/10.3390/en16020813.

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The speech intelligibility properties of classrooms greatly influence the learning process of students. Proper acoustics can promote the inclusion of foreign students and children with learning or hearing impairments. While awareness of the topic is increasing, there is still no parameter that can describe all aspects of speech transmission inside a room. This complicates the design of classrooms and requires designers to have extensive knowledge of theory and experience. In the scientific and technical literature, there is a lack of predictive tools, easy to use by designers, which can guide the choices in the early design stages in order to move towards technical solutions able to ensure adequate levels of speech intelligibility. For this reason, in this paper, the most relevant speech intelligibility parameters found in the literature were collected and discussed. Among these, the Clarity index and Speech Transmission Index were singled out as the most effective ones, whose prediction can be made with relatively simple methods. They were then analyzed through their prediction formulas, and a tool was proposed to allow an easy estimation of the minimum total equivalent sound absorption area needed in a classroom. This tool greatly simplifies the early acoustics design stage, allowing the intelligibility of speech within a classroom to be increased without requiring much theoretical effort on the part of the designers.

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Bernstein, Joshua G. W., Van Summers, Elena Grassi, and Ken W. Grant. "Auditory Models of Suprathreshold Distortion and Speech Intelligibility in Persons with Impaired Hearing." Journal of the American Academy of Audiology 24, no. 04 (April 2013): 307–28. http://dx.doi.org/10.3766/jaaa.24.4.6.

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Background: Hearing-impaired (HI) individuals with similar ages and audiograms often demonstrate substantial differences in speech-reception performance in noise. Traditional models of speech intelligibility focus primarily on average performance for a given audiogram, failing to account for differences between listeners with similar audiograms. Improved prediction accuracy might be achieved by simulating differences in the distortion that speech may undergo when processed through an impaired ear. Although some attempts to model particular suprathreshold distortions can explain general speech-reception deficits not accounted for by audibility limitations, little has been done to model suprathreshold distortion and predict speech-reception performance for individual HI listeners. Auditory-processing models incorporating individualized measures of auditory distortion, along with audiometric thresholds, could provide a more complete understanding of speech-reception deficits by HI individuals. A computational model capable of predicting individual differences in speech-recognition performance would be a valuable tool in the development and evaluation of hearing-aid signal-processing algorithms for enhancing speech intelligibility. Purpose: This study investigated whether biologically inspired models simulating peripheral auditory processing for individual HI listeners produce more accurate predictions of speech-recognition performance than audiogram-based models. Research Design: Psychophysical data on spectral and temporal acuity were incorporated into individualized auditory-processing models consisting of three stages: a peripheral stage, customized to reflect individual audiograms and spectral and temporal acuity; a cortical stage, which extracts spectral and temporal modulations relevant to speech; and an evaluation stage, which predicts speech-recognition performance by comparing the modulation content of clean and noisy speech. To investigate the impact of different aspects of peripheral processing on speech predictions, individualized details (absolute thresholds, frequency selectivity, spectrotemporal modulation [STM] sensitivity, compression) were incorporated progressively, culminating in a model simulating level-dependent spectral resolution and dynamic-range compression. Study Sample: Psychophysical and speech-reception data from 11 HI and six normal-hearing listeners were used to develop the models. Data Collection and Analysis: Eleven individualized HI models were constructed and validated against psychophysical measures of threshold, frequency resolution, compression, and STM sensitivity. Speech-intelligibility predictions were compared with measured performance in stationary speech-shaped noise at signal-to-noise ratios (SNRs) of −6, −3, 0, and 3 dB. Prediction accuracy for the individualized HI models was compared to the traditional audibility-based Speech Intelligibility Index (SII). Results: Models incorporating individualized measures of STM sensitivity yielded significantly more accurate within-SNR predictions than the SII. Additional individualized characteristics (frequency selectivity, compression) improved the predictions only marginally. A nonlinear model including individualized level-dependent cochlear-filter bandwidths, dynamic-range compression, and STM sensitivity predicted performance more accurately than the SII but was no more accurate than a simpler linear model. Predictions of speech-recognition performance simultaneously across SNRs and individuals were also significantly better for some of the auditory-processing models than for the SII. Conclusions: A computational model simulating individualized suprathreshold auditory-processing abilities produced more accurate speech-intelligibility predictions than the audibility-based SII. Most of this advantage was realized by a linear model incorporating audiometric and STM-sensitivity information. Although more consistent with known physiological aspects of auditory processing, modeling level-dependent changes in frequency selectivity and gain did not result in more accurate predictions of speech-reception performance.

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Jin, In-Ki, James M. Kates, and Kathryn H. Arehart. "Sensitivity of the Speech Intelligibility Index to the Assumed Dynamic Range." Journal of Speech, Language, and Hearing Research 60, no. 6 (June 10, 2017): 1674–80. http://dx.doi.org/10.1044/2017_jslhr-h-16-0348.

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Purpose This study aims to evaluate the sensitivity of the speech intelligibility index (SII) to the assumed speech dynamic range (DR) in different languages and with different types of stimuli. Method Intelligibility prediction uses the absolute transfer function (ATF) to map the SII value to the predicted intelligibility for a given stimuli. To evaluate the sensitivity of the predicted intelligibility to the assumed DR, ATF-transformed SII scores for English (words), Korean (sentences), and Mandarin (sentences) were derived for DRs ranging from 10 dB to 60 dB. Results Increasing the assumed DR caused steeper ATFs for all languages. However, high correlation coefficients between predicted and measured intelligibility scores were observed for DRs from 20 dB to 60 dB for ATFs in English, Korean, and Mandarin. Conclusions Results of the present study indicate that the intelligibility computed from the SII is not sensitive to the assumed DR. The 30-dB DR commonly used in computing the SII is thus a reasonable assumption that produces accurate predictions for different languages and different types of stimuli.

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Kim, Gwang Min, and Jae Hee Lee. "Prediction of Software-Based Sentence-in-Noise Recognition Thresholds of Hearing-Impaired Listeners." Audiology and Speech Research 16, no. 2 (April 30, 2020): 140–46. http://dx.doi.org/10.21848/asr.200015.

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Purpose: Although hearing-impaired (HI) listeners often have difficulty understanding in noise as their primary complaints, the speech-in-noise intelligibility test is not conducted as a standard audiologic test battery. This study investigated whether the speech audiometry in quiet accurately reflects the sentence-in-noise intelligibility of HI listeners. Methods: Sixty-two HI listeners participated. All the HI listeners had symmetrical high-frequency hearing loss and bilaterally worn hearing aids. Twenty-five normal-hearing (NH) listeners also participated as a control group. The unaided word and sentence recognition scores (WRS and SRS) were obtained in quiet at individually determined most comfortable loudness level. With bilateral hearing aids, the aided WRS and SRS were evaluated at a normal conversational level. The software-based Korean Matrix sentence in noise test was administered at a fixed level (65 dB SPL) of noise while adjusting the sentence level adaptively based on the listener’s response. The signal-to-noise ratio (SNR) required to achieve 50% intelligibility (speech recognition thresholds, SRTs) was obtained. Results: On average, the aided SRT of HI listeners was 0.1 dB SNR, and the mean SRT of NH adults was -8.91 dB SNR. The Matrix sentence-in-noise intelligibility was not sufficiently explained by the unaided WRS or unaided SRS. Conclusion: A traditional measure of the unaided speech-in-quiet recognition cannot accurately predict the aided speech-innoise intelligibility. Clinically, a software-based sentence-in-noise intelligibility test is recommended to directly confirm the actual benefits of hearing aid in noisy situations.

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Rennies, Jan, Anna Warzybok, Thomas Brand, and Birger Kollmeier. "Measurement and Prediction of Binaural-Temporal Integration of Speech Reflections." Trends in Hearing 23 (January 2019): 233121651985426. http://dx.doi.org/10.1177/2331216519854267.

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For speech intelligibility in rooms, the temporal integration of speech reflections is typically modeled by separating the room impulse response (RIR) into an early (assumed beneficial for speech intelligibility) and a late part (assumed detrimental). This concept was challenged in this study by employing binaural RIRs with systematically varied interaural phase differences (IPDs) and amplitude of the direct sound and a variable number of reflections delayed by up to 200 ms. Speech recognition thresholds in stationary noise were measured in normal-hearing listeners for 86 conditions. The data showed that direct sound and one or several early speech reflections could be perfectly integrated when they had the same IPD. Early reflections with the same IPD as the noise (but not as the direct sound) could not be perfectly integrated with the direct sound. All conditions in which the dominant speech information was within the early RIR components could be well predicted by a binaural speech intelligibility model using classic early/late separation. In contrast, when amplitude or IPD favored late RIR components, listeners appeared to be capable of focusing on these components rather than on the precedent direct sound. This could not be modeled by an early/late separation window but required a temporal integration window that can be flexibly shifted along the RIR.

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Kang, Okim, Kevin Hirschi, John H. Hansen, and Stephen Looney. "Characterization and normalization of second language speech intelligibility through lexical stress, speech rate, rhythm, and pauses." Journal of the Acoustical Society of America 152, no. 4 (October 2022): A265. http://dx.doi.org/10.1121/10.0016224.

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While a range of measures based on speech production, language, and perception are possible (Manun et al., 2020) for the prediction and estimation of speech intelligibility, what constitutes second language (L2) intelligibility remains under-defined. Prosodic and temporal features (i.e., stress, speech rate, rhythm, and pause placement) have been shown to impact listener perception (Kang et al., 2020). Still, their relationship with highly intelligible speech is yet unclear. This study aimed to characterize L2 speech intelligibility. Acoustic analyses, including PRAAT and Python scripts, were conducted on 405 speech samples (30 s) from 102 L2 English speakers with a wide variety of backgrounds, proficiency levels, and intelligibility levels. The results indicate that highly intelligible speakers of English employ between 2 and 4 syllables per second and that higher or lower speeds are less intelligible. Silent pauses between 0.3 and 0.8 s were associated with the highest levels of intelligibility. Rhythm, measured by Δ syllable length of all content syllables, was marginally associated with intelligibility. Finally, lexical stress accuracy did not interfere substantially with intelligibility until less than 70% of the polysyllabic words were incorrect. These findings inform the fields of first and second language research as well as language education and pathology.

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Ludvigsen, Carl, Claus Elberling, Gitte Keidser, and Torben Poulsen. "Prediction of Intelligibility of Non-linearly Processed Speech." Acta Oto-Laryngologica 109, sup469 (January 1, 1990): 190–95. http://dx.doi.org/10.1080/00016489.1990.12088428.

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Andersen, Asger Heidemann, Jan Mark de Haan, Zheng-Hua Tan, and Jesper Jensen. "Nonintrusive Speech Intelligibility Prediction Using Convolutional Neural Networks." IEEE/ACM Transactions on Audio, Speech, and Language Processing 26, no. 10 (October 2018): 1925–39. http://dx.doi.org/10.1109/taslp.2018.2847459.

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Edraki, Amin, Wai-Yip Chan, Jesper Jensen, and Daniel Fogerty. "Speech Intelligibility Prediction Using Spectro-Temporal Modulation Analysis." IEEE/ACM Transactions on Audio, Speech, and Language Processing 29 (2021): 210–25. http://dx.doi.org/10.1109/taslp.2020.3039929.

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Müsch, Hannes, and Mary Florentine. "So/ren Buus’ contribution to speech intelligibility prediction." Journal of the Acoustical Society of America 117, no. 4 (April 2005): 2453. http://dx.doi.org/10.1121/1.4787126.

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Schwerin, Belinda, and Kuldip Paliwal. "An improved speech transmission index for intelligibility prediction." Speech Communication 65 (November 2014): 9–19. http://dx.doi.org/10.1016/j.specom.2014.05.003.

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Ahnert, Wolfgang, and Tobias Behrens. "Speech intelligibility prediction in very large sacral venues." Journal of the Acoustical Society of America 133, no. 5 (May 2013): 3531. http://dx.doi.org/10.1121/1.4806366.

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Samar, Vincent J., and Dale Evan Metz. "Criterion Validity of Speech Intelligibility Rating-Scale Procedures for the Hearing-Impaired Population." Journal of Speech, Language, and Hearing Research 31, no. 3 (September 1988): 307–16. http://dx.doi.org/10.1044/jshr.3103.307.

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The criterion validity and reliability of two popular rating-scale procedures for the assessment of the contextual speech intelligibility of hearing-impaired individuals (The NTID Scales) were studied under clinically typical conditions of test administration and evaluation. The criterion measure was a write-down procedure based on subjects' readings of sentence lists chosen from The CID Everyday Sentence lists. Although the results revealed generally high overall validity and reliability coefficients for the two scales, a close examination of the distribution of estimation error over the full range of rating-scale values revealed gross violations of measurement prediction within the clinically most frequent midrange of speech intelligibility. The results indicate that the rating-scale procedure significantly compromises clinical and research classification of an individual's speech intelligibility and that write-down procedures may provide a viable and significantly more accurate alternative for speech intelligibility assessment.

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Oh, Hongyeop, Soon-Je Choi, and In-Ki Jin. "Effects of Contextual Predictability Clues in Speech Materials on the Korean Speech Intelligibility Index." Audiology and Speech Research 16, no. 3 (July 31, 2020): 217–25. http://dx.doi.org/10.21848/asr.200021.

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Purpose: This study aimed to derive band-importance functions (BIFs) and transfer functions (TFs) according to contextual predictability clues to determine the influence of contextual predictability clues in Korean speech material on the speech intelligibility index (SII). Methods: This study was conducted on 156 native speakers of Korean who had normal hearing. Korean speech perception in noise test material, which was composed of 120 high-predictability and 120 low-predictability sentences, was used for stimuli. To obtain intelligibility data, participants were tested for intelligibility in various frequency ranges and signal-to-noise ratio conditions. In order to derive the BIF and the TF, a nonlinear optimization procedure using MATLAB (MathWorks, Inc.) was used. Results: The BIF derived from the high-predictability sentences showed a peak in areas of 700 Hz (7.0%), 1,850 Hz (8.5%), and 4,800 Hz (7.6%). The crossover frequency for the high-predictability sentences was around 1,370 Hz. The BIF derived from the low-predictability sentences showed a peak in areas of 570 Hz (7.5%), 1,850 Hz (9.3%), and 4,000 Hz (8.0%). The crossover frequency for the low-predictability sentences was around 1,600 Hz. In the case of the TF, the TF curves derived from high-predictability sentences were steeper than those derived from low-predictability sentences.Conclusion: In the SII model, speech intelligibility differs according to contextual predictability clues. Especially, the more contextual predictability clues at the identical audibility, the higher the intelligibility predicted by the SII. Therefore, accurate speech intelligibility prediction requires the use of SII considering the contextual predictability clues that are characteristic of the stimulus.

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Morrison, H. Boyd, and John G. Casali. "Intelligibility of Synthesized Voice Messages in Commercial Truck Cab Noise for Normal-Hearing and Hearing-Impaired Listeners." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 38, no. 14 (October 1994): 801–5. http://dx.doi.org/10.1177/154193129403801401.

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A human factors experiment was conducted to assess the intelligibility of synthesized speech under a variety of noise conditions for both hearing-impaired and normal-hearing subjects. Modified Rhyme Test stimuli were used to determine intelligibility in four speech-to-noise (S/N) ratios (0,5,10, and 15 dB), and three noise types, consisting of flat-by-octaves (pink) noise, interior noise of a currently produced heavy truck, and truck cab noise with added background speech. A quiet condition was also investigated. During recording of the truck noise for the experiment, in-cab noise measurements were obtained. According to OSHA standards, these data indicated that drivers of the sampled trucks have a minimal risk for noise-induced hearing loss due to in-cab noise exposure when driving at freeway speeds because noise levels were below 80 dBA. In the intelligibility experiment, subjects with hearing loss had significantly lower intelligibility than normal-hearing subjects, both in quiet and in noise, but no interaction with noise type or S/N ratio was found. Intelligibility was significantly lower for the noise with background speech than the other noises, but the truck noise produced intelligibility equal to the pink noise. An analytical prediction of intelligibility using Articulation Index calculations exhibited a high positive correlation with the empirically obtained intelligibility data for both groups of subjects.

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Castro Martinez, Angel Mario, Constantin Spille, Jana Roßbach, Birger Kollmeier, and Bernd T. Meyer. "Prediction of speech intelligibility with DNN-based performance measures." Computer Speech & Language 74 (July 2022): 101329. http://dx.doi.org/10.1016/j.csl.2021.101329.

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van Wijngaarden, Sander J., and Rob Drullman. "Binaural intelligibility prediction based on the speech transmission index." Journal of the Acoustical Society of America 123, no. 6 (June 2008): 4514–23. http://dx.doi.org/10.1121/1.2905245.

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Lavandier, Mathieu, and John F. Culling. "Prediction of binaural speech intelligibility against noise in rooms." Journal of the Acoustical Society of America 127, no. 1 (January 2010): 387–99. http://dx.doi.org/10.1121/1.3268612.

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Hines, Andrew, and Naomi Harte. "Speech intelligibility prediction using a Neurogram Similarity Index Measure." Speech Communication 54, no. 2 (February 2012): 306–20. http://dx.doi.org/10.1016/j.specom.2011.09.004.

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Bernstein, Joshua G. W., Golbarg Mehraei, Shihab Shamma, Frederick J. Gallun, Sarah M. Theodoroff, and Marjorie R. Leek. "Spectrotemporal Modulation Sensitivity as a Predictor of Speech Intelligibility for Hearing-Impaired Listeners." Journal of the American Academy of Audiology 24, no. 04 (April 2013): 293–306. http://dx.doi.org/10.3766/jaaa.24.4.5.

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Background: A model that can accurately predict speech intelligibility for a given hearing-impaired (HI) listener would be an important tool for hearing-aid fitting or hearing-aid algorithm development. Existing speech-intelligibility models do not incorporate variability in suprathreshold deficits that are not well predicted by classical audiometric measures. One possible approach to the incorporation of such deficits is to base intelligibility predictions on sensitivity to simultaneously spectrally and temporally modulated signals. Purpose: The likelihood of success of this approach was evaluated by comparing estimates of spectrotemporal modulation (STM) sensitivity to speech intelligibility and to psychoacoustic estimates of frequency selectivity and temporal fine-structure (TFS) sensitivity across a group of HI listeners. Research Design: The minimum modulation depth required to detect STM applied to an 86 dB SPL four-octave noise carrier was measured for combinations of temporal modulation rate (4, 12, or 32 Hz) and spectral modulation density (0.5, 1, 2, or 4 cycles/octave). STM sensitivity estimates for individual HI listeners were compared to estimates of frequency selectivity (measured using the notched-noise method at 500, 1000, 2000, and 4000 Hz), TFS processing ability (2 Hz frequency-modulation detection thresholds for 500, 1000, 2000, and 4000 Hz carriers) and sentence intelligibility in noise (at a 0 dB signal-to-noise ratio) that were measured for the same listeners in a separate study. Study Sample: Eight normal-hearing (NH) listeners and 12 listeners with a diagnosis of bilateral sensorineural hearing loss participated. Data Collection and Analysis: STM sensitivity was compared between NH and HI listener groups using a repeated-measures analysis of variance. A stepwise regression analysis compared STM sensitivity for individual HI listeners to audiometric thresholds, age, and measures of frequency selectivity and TFS processing ability. A second stepwise regression analysis compared speech intelligibility to STM sensitivity and the audiogram-based Speech Intelligibility Index. Results: STM detection thresholds were elevated for the HI listeners, but only for low rates and high densities. STM sensitivity for individual HI listeners was well predicted by a combination of estimates of frequency selectivity at 4000 Hz and TFS sensitivity at 500 Hz but was unrelated to audiometric thresholds. STM sensitivity accounted for an additional 40% of the variance in speech intelligibility beyond the 40% accounted for by the audibility-based Speech Intelligibility Index. Conclusions: Impaired STM sensitivity likely results from a combination of a reduced ability to resolve spectral peaks and a reduced ability to use TFS information to follow spectral-peak movements. Combining STM sensitivity estimates with audiometric threshold measures for individual HI listeners provided a more accurate prediction of speech intelligibility than audiometric measures alone. These results suggest a significant likelihood of success for an STM-based model of speech intelligibility for HI listeners.

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Abdullah, Abdul Hakim, and Zamir A. Zulkefli. "A Study of the Acoustics and Speech Intelligibility Quality of Mosques in Malaysia." Applied Mechanics and Materials 564 (June 2014): 129–34. http://dx.doi.org/10.4028/www.scientific.net/amm.564.129.

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This study presents the assessment of the quality of speech intelligibility of two Malaysian mosques and the results are used to develop a set of general acoustical guidelines to be used in the design of a mosque. Two mosques were selected for the research: Masjid UPM and the Masjid Jamek. The objective of the research is to enable the comparison of the acoustics and speech intelligibility between the mosques as function of the size, volume, occupancy and other parameters of the main prayer hall on the acoustic and speech intelligibility of the respective mosques. The reverberation time (RT60), speech level (SL), background noise (BN), signal-to-noise ratio (S/N ratio) were determined and are used to develop the speech transmission index (STI) and rapid transmission index (RASTI) prediction models for both mosques. It was observed from the results that the RT60, STI and RASTI values shows better performance over number of occupancy for both mosques. Furthermore, the BN and SL results were visualized using the spatial distribution patterns (SDP) of the main hall. The results of the analysis show that the overall acoustic and speech quality of Masjid Jamek is better when compared to the overall acoustic and speech quality of Masjid UPM. These results are then used to develop a set of design recommendations to ensure adequate speech intelligibility quality a mosque.

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Schädler, Marc René, Anna Warzybok, Sabine Hochmuth, and Birger Kollmeier. "Matrix sentence intelligibility prediction using an automatic speech recognition system." International Journal of Audiology 54, sup2 (May 2015): 100–107. http://dx.doi.org/10.3109/14992027.2015.1061708.

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Karbasi, Mahdie, Steffen Zeiler, and Dorothea Kolossa. "Microscopic and Blind Prediction of Speech Intelligibility: Theory and Practice." IEEE/ACM Transactions on Audio, Speech, and Language Processing 30 (2022): 2141–55. http://dx.doi.org/10.1109/taslp.2022.3184888.

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Whitmal, Nathaniel A., and Kristina DeRoy. "Adaptive bandwidth measurements of importance functions for speech intelligibility prediction." Journal of the Acoustical Society of America 130, no. 6 (December 2011): 4032–43. http://dx.doi.org/10.1121/1.3641453.

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Rogers, Catherine L., and Jonathan M. Dalby. "Prediction of foreign‐accented speech intelligibility from segmental contrast measures." Journal of the Acoustical Society of America 100, no. 4 (October 1996): 2725. http://dx.doi.org/10.1121/1.416179.

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Biberger, Thomas, and Stephan D. Ewert. "Envelope-power based prediction of auditory masking and speech intelligibility." Journal of the Acoustical Society of America 137, no. 4 (April 2015): 2207. http://dx.doi.org/10.1121/1.4920034.

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Kokabi, Omid, Fabian Brinkmann, and Stefan Weinzierl. "Segmentation of binaural room impulse responses for speech intelligibility prediction." Journal of the Acoustical Society of America 144, no. 5 (November 2018): 2793–800. http://dx.doi.org/10.1121/1.5078598.

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Kokabi, Omid, Fabian Brinkmann, and Stefan Weinzierl. "Prediction of speech intelligibility using pseudo-binaural room impulse responses." Journal of the Acoustical Society of America 145, no. 4 (April 2019): EL329—EL333. http://dx.doi.org/10.1121/1.5099169.

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Olson, Bruce C., and Ana M. Jaramillo. "Prediction of speech intelligibility through the use of simulation tools." Journal of the Acoustical Society of America 140, no. 4 (October 2016): 3069. http://dx.doi.org/10.1121/1.4969561.

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Dance, Stephen, and Roger Dentoni. "The prediction of speech intelligibility in classrooms using computer models." Journal of the Acoustical Society of America 117, no. 4 (April 2005): 2406. http://dx.doi.org/10.1121/1.4786175.

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Christiansen, Claus, Michael Syskind Pedersen, and Torsten Dau. "Prediction of speech intelligibility based on an auditory preprocessing model." Speech Communication 52, no. 7-8 (July 2010): 678–92. http://dx.doi.org/10.1016/j.specom.2010.03.004.

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Kobayashi, Yosuke, and Kazuhiro Kondo. "Japanese speech intelligibility estimation and prediction using objective intelligibility indices under noisy and reverberant conditions." Applied Acoustics 156 (December 2019): 327–35. http://dx.doi.org/10.1016/j.apacoust.2019.07.034.

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Wu, Yu-Hsiang, Elizabeth Stangl, Carol Pang, and Xuyang Zhang. "The Effect of Audiovisual and Binaural Listening on the Acceptable Noise Level (ANL): Establishing an ANL Conceptual Model." Journal of the American Academy of Audiology 25, no. 02 (February 2014): 141–53. http://dx.doi.org/10.3766/jaaa.25.2.3.

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Background: Little is known regarding the acoustic features of a stimulus used by listeners to determine the acceptable noise level (ANL). Features suggested by previous research include speech intelligibility (noise is unacceptable when it degrades speech intelligibility to a certain degree; the intelligibility hypothesis) and loudness (noise is unacceptable when the speech-to-noise loudness ratio is poorer than a certain level; the loudness hypothesis). Purpose: The purpose of the study was to investigate if speech intelligibility or loudness is the criterion feature that determines ANL. To achieve this, test conditions were chosen so that the intelligibility and loudness hypotheses would predict different results. In Experiment 1, the effect of audiovisual (AV) and binaural listening on ANL was investigated; in Experiment 2, the effect of interaural correlation (ρ) on ANL was examined. Research Design: A single-blinded, repeated-measures design was used. Study Sample: Thirty-two and twenty-five younger adults with normal hearing participated in Experiments 1 and 2, respectively. Data Collection and Analysis: In Experiment 1, both ANL and speech recognition performance were measured using the AV version of the Connected Speech Test (CST) in three conditions: AV-binaural, auditory only (AO)-binaural, and AO-monaural. Lipreading skill was assessed using the Utley lipreading test. In Experiment 2, ANL and speech recognition performance were measured using the Hearing in Noise Test (HINT) in three binaural conditions, wherein the interaural correlation of noise was varied: ρ = 1 (NoSo [a listening condition wherein both speech and noise signals are identical across two ears]), −1 (NπSo [a listening condition wherein speech signals are identical across two ears whereas the noise signals of two ears are 180 degrees out of phase]), and 0 (NuSo [a listening condition wherein speech signals are identical across two ears whereas noise signals are uncorrelated across ears]). The results were compared to the predictions made based on the intelligibility and loudness hypotheses. Results: The results of the AV and AO conditions appeared to support the intelligibility hypothesis due to the significant correlation between visual benefit in ANL (AV re: AO ANL) and (1) visual benefit in CST performance (AV re: AO CST) and (2) lipreading skill. The results of the NoSo, NπSo, and NuSo conditions negated the intelligibility hypothesis because binaural processing benefit (NπSo re: NoSo, and NuSo re: NoSo) in ANL was not correlated to that in HINT performance. Instead, the results somewhat supported the loudness hypothesis because the pattern of ANL results across the three conditions (NoSo ≈ NπSo ≈ NuSo ANL) was more consistent with what was predicted by the loudness hypothesis (NoSo ≈ NπSo < NuSo ANL) than by the intelligibility hypothesis (NπSo < NuSo < NoSo ANL). The results of the binaural and monaural conditions supported neither hypothesis because (1) binaural benefit (binaural re: monaural) in ANL was not correlated to that in speech recognition performance, and (2) the pattern of ANL results across conditions (binaural < monaural ANL) was not consistent with the prediction made based on previous binaural loudness summation research (binaural ≥ monaural ANL). Conclusions: The study suggests that listeners may use multiple acoustic features to make ANL judgments. The binaural/monaural results showing that neither hypothesis was supported further indicate that factors other than speech intelligibility and loudness, such as psychological factors, may affect ANL. The weightings of different acoustic features in ANL judgments may vary widely across individuals and listening conditions.

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Samlan, Robin A., and Gary Weismer. "The Relationship of Selected Perceptual Measures of Diadochokinesis to Speech Intelligibility in Dysarthric Speakers With Amyotrophic Lateral Sclerosis." American Journal of Speech-Language Pathology 4, no. 2 (May 1995): 9–13. http://dx.doi.org/10.1044/1058-0360.0402.09.

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The current experiment explored the relationship of two perceptual measures of diadochokinetic (DDK) performance to speech intelligibility in 15 men with amyotrophic lateral sclerosis (ALS). The perceptual measures of DDK performance took the form of scalings of articulatory precision and rhythmic consistency. Regression analyses indicated that both measures were statistically significant in their ability to predict scaled speech intelligibility, although the efficiency of that prediction was somewhat better for articulatory precision than for rhythmic consistency. Regressions involving articulatory precision and rhythmic consistency were also found to be statistically significant. These results are discussed in terms of the clinical significance of DDK measures, especially their potential independence (or lack thereof) from general estimates of speech severity.

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Gordon-Brannan, Mary, and Barbara Williams Hodson. "Intelligibility/Severity Measurements of Prekindergarten Children’s Speech." American Journal of Speech-Language Pathology 9, no. 2 (May 2000): 141–50. http://dx.doi.org/10.1044/1058-0360.0902.141.

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Intelligibility/severity measurements were obtained for 48 prekindergarten children with varying levels of phonological proficiency/ deficiency. The measure used as the “standard” was percentage of words understood (i.e., orthographically transcribed correctly) in continuous speech in a known context by unfamiliar trained listeners. The children were divided into four groups based on the percentage of words understood from their continuous speech samples. The ranges of intelligibility for each group were: (a) 91–100% for children with “adult-like” speech; (b) 83–90% for children in the “mild” category; (c) 68–81% for children with moderate intelligibility/speech involvement; and (d) 16–63% for the 12 children in the “severe” (i.e., least intelligible) category. When the percentages of the children in the severe group were excluded, the range of the top three groups combined was 68–100% and the mean was 85%. For a child 4 years of age or older, any percentage of words understood in connected speech that falls below 66% (2 standard deviations below the mean) may be a potential indicator of speech difficulty. In addition, data were obtained from the 48 children to determine the correlations between the standard measure and the following intelligibility/severity measures: (a) imitated sentences, (b) imitated words, (c) listener ratings of intelligibility, and (d) phonological deviation averages. All five measures, including the standard measure, investigated in this study were strongly intercorrelated. Multiple regression analysis results yielded a prediction model that included listener ratings and imitated sentences measures. Results of multivariate analysis of variance (MANOVA), univariate analysis, and post-hoc Bonferroni tests indicated that differences between all pairs of groups were significant for the listener rating measure based on the continuous speech sample. For the percentage of words understood in continuous speech samples, the differences between all pairs of groups, except between the adult-like and mild groups, were also significant. The only group that differed significantly from the other three groups for all five measures was the severe group.

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Rӧttges, Saskia, Christopher F. Hauth, Jan Rennies, and Thomas Brand. "Using a blind EC mechanism for modelling the interaction between binaural and temporal speech processing." Acta Acustica 6 (2022): 21. http://dx.doi.org/10.1051/aacus/2022009.

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We reanalyzed a study that investigated binaural and temporal integration of speech reflections with different amplitudes, delays, and interaural phase differences. We used a blind binaural speech intelligibility model (bBSIM), applying an equalization-cancellation process for modeling binaural release from masking. bBSIM is blind, as it requires only the mixed binaural speech and noise signals and no auxiliary information about the listening conditions. bBSIM was combined with two non-blind back-ends: The speech intelligibility index (SII) and the speech transmission index (STI) resulting in hybrid-models. Furthermore, bBSIM was combined with the non-intrusive short-time objective intelligibility (NI-STOI) resulting in a fully blind model. The fully non-blind reference model used in the previous study achieved the best prediction accuracy (R2 = 0.91 and RMSE = 1 dB). The fully blind model yielded a coefficient of determination (R2 = 0.87) similar to that of the reference model but also the highest root mean square error of the models tested in this study (RMSE = 4.4 dB). By adjusting the binaural processing errors of bBSIM as done in the reference model, the RMSE could be decreased to 1.9 dB. Furthermore, in this study, the dynamic range of the SII had to be adjusted to predict the low SRTs of the speech material used.

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Genta, G., A. Astolf, P. Bottalico, G. Barbato, and R. Levi. "Management of Truncated Data in Speech Transmission Evaluation for Pupils in Classrooms." Measurement Science Review 13, no. 2 (April 1, 2013): 75–82. http://dx.doi.org/10.2478/msr-2013-0012.

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Speech intelligibility is a subjective performance index defined as the percentage of a message understood correctly. Often the results of speech intelligibility tests would suggest that conditions are acceptable, with Intelligibility Score (IS) of the order of 90% or more, while speech transmission performance may not be satisfactory. Subjective ratings of the Listening Easiness Score (LES), based on a discrete questionnaire, provide an alternative approach. A total of 239 primary school pupils, aged 7 to 11, evenly distributed among the grades, participated in the survey. The objective indicator Speech Transmission Index (STI) was also measured for each test setting in seven different positions in the laboratory classroom used for the test. Both IS and LES are inherently bounded, and their data distributions exhibit a significant accumulation of scores in the upper and lower parts. The resulting truncation problem has been addressed with a method based on the normal probability plot, enabling identification of mathematical models relating IS and LES to STI, as well as the estimation of related uncertainties. IS and LES exhibit substantially similar metrological capabilities, as, for both, model relative uncertainty does not exceed 4% and uncertainties in prediction of new observations are about twice as large.

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Ludvigsen, Carl. "Prediction of speech intelligibility for normal‐hearing and cochlear‐impaired listeners." Journal of the Acoustical Society of America 77, S1 (April 1985): S68—S69. http://dx.doi.org/10.1121/1.2022467.

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Biberger, Thomas, and Stephan D. Ewert. "Envelope and intensity based prediction of psychoacoustic masking and speech intelligibility." Journal of the Acoustical Society of America 140, no. 2 (August 2016): 1023–38. http://dx.doi.org/10.1121/1.4960574.

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Beutelmann, Rainer, Thomas Brand, and Birger Kollmeier. "Prediction of binaural speech intelligibility with frequency-dependent interaural phase differences." Journal of the Acoustical Society of America 126, no. 3 (September 2009): 1359–68. http://dx.doi.org/10.1121/1.3177266.

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Hodgson, Murray. "Prediction of speech intelligibility in rooms—a comparison of five methods." Journal of the Acoustical Society of America 116, no. 4 (October 2004): 2638. http://dx.doi.org/10.1121/1.4785523.

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Taal, Cees H., Richard C. Hendriks, Richard Heusdens, and Jesper Jensen. "An Algorithm for Intelligibility Prediction of Time–Frequency Weighted Noisy Speech." IEEE Transactions on Audio, Speech, and Language Processing 19, no. 7 (September 2011): 2125–36. http://dx.doi.org/10.1109/tasl.2011.2114881.

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Mamun, Nursadul, Wissam A. Jassim, and Muhammad S. A. Zilany. "Prediction of Speech Intelligibility Using a Neurogram Orthogonal Polynomial Measure (NOPM)." IEEE/ACM Transactions on Audio, Speech, and Language Processing 23, no. 4 (April 2015): 760–73. http://dx.doi.org/10.1109/taslp.2015.2401513.

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Ellaham, Nicolas N., Christian Giguère, and Wail Gueaieb. "Prediction of binaural speech intelligibility when using non‐linear hearing aids." Journal of the Acoustical Society of America 127, no. 3 (March 2010): 1848. http://dx.doi.org/10.1121/1.3384362.

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Journal articles on the topic 'Speech intelligibility prediction'

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