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Using Automatic Speech Recognition to Optimize Hearing-Aid Time Constants
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In: ISSN: 1662-4548 ; EISSN: 1662-453X ; Frontiers in Neuroscience ; https://hal.archives-ouvertes.fr/hal-03627441 ; Frontiers in Neuroscience, Frontiers, 2022, 16 (779062), ⟨10.3389/fnins.2022.779062⟩ ; https://www.frontiersin.org/articles/10.3389/fnins.2022.779062/full (2022)
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Abstract:
Edited by: Qinglin Meng, South China University of Technology, China ; International audience ; Automatic speech recognition (ASR), when combined with hearing-aid (HA) and hearing-loss (HL) simulations, can predict aided speech-identification performances of persons with age-related hearing loss. ASR can thus be used to evaluate different HA configurations, such as combinations of insertion-gain functions and compression thresholds, in order to optimize HA fitting for a given person. The present study investigated whether, after fixing compression thresholds and insertion gains, a random-search algorithm could be used to optimize time constants (i.e., attack and release times) for 12 audiometric profiles. The insertion gains were either those recommended by the CAM2 prescription rule or those optimized using ASR, while compression thresholds were always optimized using ASR. For each audiometric profile, the random-search algorithm was used to vary time constants with the aim to maximize ASR performance. A HA simulator and a HL simulator simulator were used, respectively, to amplify and to degrade speech stimuli according to the input audiogram. The resulting speech signals were fed to an ASR system for recognition. For each audiogram, 1,000 iterations of the random-search algorithm were used to find the time-constant configuration yielding the highest ASR score. To assess the reproducibility of the results, the random search algorithm was run twice. Optimizing the time constants significantly improved the ASR scores when CAM2 insertion gains were used, but not when using ASR-based gains. Repeating the random search yielded similar ASR scores, but different time-constant configurations.
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Keyword:
[INFO]Computer Science [cs]; age-related hearing loss (ARHL); attack time; automatic speech recognition (ASR); compression speed; hearing aids (HAs); random search (RS); release time
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URL: https://doi.org/10.3389/fnins.2022.779062
https://hal.archives-ouvertes.fr/hal-03627441
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| 2 |
RETRIEVING SPEAKER INFORMATION FROM PERSONALIZED ACOUSTIC MODELS FOR SPEECH RECOGNITION
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In: IEEE ICASSP 2022 ; https://hal.archives-ouvertes.fr/hal-03539741 ; IEEE ICASSP 2022, 2022, Singapour, Singapore (2022)
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| 3 |
Fine-tuning pre-trained models for Automatic Speech Recognition: experiments on a fieldwork corpus of Japhug (Trans-Himalayan family)
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In: https://halshs.archives-ouvertes.fr/halshs-03647315 ; 2022 (2022)
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| 6 |
Treasure Hunters 2: exploration of speech training efficacy ...
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| 7 |
MLLP-VRAIN Spanish ASR Systems for the Albayzín-RTVE 2020 Speech-to-Text Challenge: Extension
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In: Applied Sciences; Volume 12; Issue 2; Pages: 804 (2022)
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| 8 |
Evaluating Novel Speech Transcription Architectures on the Spanish RTVE2020 Database
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In: Applied Sciences; Volume 12; Issue 4; Pages: 1889 (2022)
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| 9 |
Automatic Speech Recognition Performance Improvement for Mandarin Based on Optimizing Gain Control Strategy
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In: Sensors; Volume 22; Issue 8; Pages: 3027 (2022)
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| 10 |
Automatic Speech Recognition (ASR) Systems for Children: A Systematic Literature Review
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In: Applied Sciences; Volume 12; Issue 9; Pages: 4419 (2022)
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| 11 |
An Empirical Performance Analysis of the Speak Correct Computerized Interface
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In: Processes; Volume 10; Issue 3; Pages: 487 (2022)
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| 12 |
Influence of Highly Inflected Word Forms and Acoustic Background on the Robustness of Automatic Speech Recognition for Human–Computer Interaction
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In: Mathematics; Volume 10; Issue 5; Pages: 711 (2022)
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| 13 |
Fine-tuning pre-trained models for Automatic Speech Recognition: experiments on a fieldwork corpus of Japhug (Trans-Himalayan family)
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In: https://halshs.archives-ouvertes.fr/halshs-03647315 ; 2022 (2022)
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| 15 |
Automatic Speech Recognition systems errors for accident-prone sleepiness detection through voice
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In: EUSIPCO 2021 ; https://hal.archives-ouvertes.fr/hal-03324033 ; EUSIPCO 2021, Aug 2021, Dublin (en ligne), Ireland. ⟨10.23919/EUSIPCO54536.2021.9616299⟩ (2021)
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| 16 |
Automatic Speech Recognition systems errors for objective sleepiness detection through voice
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In: Proceedings Interspeech 2021 ; Interspeech 2021 ; https://hal.archives-ouvertes.fr/hal-03328827 ; Interspeech 2021, Aug 2021, Brno (virtual), Czech Republic. pp.2476-2480, ⟨10.21437/Interspeech.2021-291⟩ (2021)
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| 17 |
LeBenchmark: A Reproducible Framework for Assessing Self-Supervised Representation Learning from Speech
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In: INTERSPEECH 2021: Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-03317730 ; INTERSPEECH 2021: Conference of the International Speech Communication Association, Aug 2021, Brno, Czech Republic (2021)
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| 18 |
LeBenchmark: A Reproducible Framework for Assessing Self-Supervised Representation Learning from Speech
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In: INTERSPEECH 2021: ; INTERSPEECH 2021: Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-03317730 ; INTERSPEECH 2021: Conference of the International Speech Communication Association, Aug 2021, Brno, Czech Republic (2021)
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| 19 |
LeBenchmark: A Reproducible Framework for Assessing Self-Supervised Representation Learning from Speech
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In: INTERSPEECH 2021: ; INTERSPEECH 2021: Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-03317730 ; INTERSPEECH 2021: Conference of the International Speech Communication Association, Aug 2021, Brno, Czech Republic (2021)
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| 20 |
Re-synchronization using the Hand Preceding Model for Multi-modal Fusion in Automatic Continuous Cued Speech Recognition
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In: ISSN: 1520-9210 ; IEEE Transactions on Multimedia ; https://hal.archives-ouvertes.fr/hal-02433830 ; IEEE Transactions on Multimedia, Institute of Electrical and Electronics Engineers, 2021, 23, pp.292-305. ⟨10.1109/TMM.2020.2976493⟩ (2021)
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