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EVOLEX : la reconnaissance vocale au service du diagnostic des dysfonctionnements langagiers
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In: Séminaire AFCP 2021 – Phonétique Clinique ; https://hal-univ-tlse3.archives-ouvertes.fr/hal-03269242 ; Séminaire AFCP 2021 – Phonétique Clinique, May 2021, Toulouse (virtuel), France ; http://www.afcp-parole.org/seminaire-afcp-phonetique-clinique-27-mai-2021/ (2021)
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Automatic extraction of speech rhythm descriptors for speech intelligibility assessment in the context of Head and Neck Cancers
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In: à paraître ; INTERSPEECH 2021 ; https://hal-univ-tlse3.archives-ouvertes.fr/hal-03269227 ; INTERSPEECH 2021, ISCA : International Speech and Communication Association, Aug 2021, Brno, Czech Republic ; https://www.interspeech2021.org (2021)
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Construction of an automatic score for the evaluation of speech disorders among patients treated for a cancer of the oral cavity or the oropharynx: The Carcinologic Speech Severity Index
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In: ISSN: 1043-3074 ; EISSN: 1097-0347 ; Head and Neck ; https://hal-univ-tlse3.archives-ouvertes.fr/hal-03413678 ; Head and Neck, Wiley, In press, ⟨10.1002/hed.26903⟩ (2021)
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C2SI corpus: a database of speech disorder productions to assess intelligibility and quality of life in head and neck cancers
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In: ISSN: 1574-020X ; EISSN: 1574-0218 ; Language Resources and Evaluation ; https://hal.archives-ouvertes.fr/hal-02921918 ; Language Resources and Evaluation, Springer Verlag, 2021, 55 (1), pp.173-190. ⟨10.1007/s10579-020-09496-3⟩ ; https://link.springer.com/article/10.1007/s10579-020-09496-3 (2021)
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Construction d'un index holistique d'impact sur la communication des troubles de la parole chez les patients traités pour un cancer oral ou oropharyngé
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In: Séminaire AFCP 2021, Thème : Phonétique Clinique ; https://hal.archives-ouvertes.fr/hal-03258582 ; Séminaire AFCP 2021, Thème : Phonétique Clinique, May 2021, Toulouse (virtuel), France. 2021 ; http://www.afcp-parole.org/seminaire-afcp-phonetique-clinique-27-mai-2021/ (2021)
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Analyse des performances des algorithmes d'estimation de la fréquence fondamentale dans le cadre de la voix pathologique
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In: Séminaire AFCP 2021 – Phonétique Clinique ; https://hal-univ-tlse3.archives-ouvertes.fr/hal-03269235 ; Séminaire AFCP 2021 – Phonétique Clinique, May 2021, Toulouse (virtuel), France ; http://www.afcp-parole.org/seminaire-afcp-phonetique-clinique-27-mai-2021/ (2021)
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L'identification automatique des différents bruits de gorge chez le sujet sain : une étude pilote
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In: Séminaire AFCP 2021 – Phonétique Clinique ; https://hal-univ-tlse3.archives-ouvertes.fr/hal-03269247 ; Séminaire AFCP 2021 – Phonétique Clinique, May 2021, Toulouse (virtuel), France ; http://www.afcp-parole.org/seminaire-afcp-phonetique-clinique-27-mai-2021/ (2021)
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Une méthode automatique non supervisée pour évaluer le score de sévérité de la parole chez les patients traités pour un cancer ORL
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In: Séminaire AFCP 2021 – Phonétique Clinique ; https://hal-univ-tlse3.archives-ouvertes.fr/hal-03269228 ; Séminaire AFCP 2021 – Phonétique Clinique, May 2021, Toulouse (virtuel), France. 2021 ; http://www.afcp-parole.org/seminaire-afcp-phonetique-clinique-27-mai-2021/ (2021)
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La laryngophoniatrie du futur
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In: Congrès National de la Société Française d'ORL ; https://hal.archives-ouvertes.fr/hal-03365266 ; Congrès National de la Société Française d'ORL, 2021, Paris, France (2021)
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La laryngophoniatrie du futur
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In: Congrès National de la Société Française d'ORL ; https://hal.archives-ouvertes.fr/hal-03365266 ; Congrès National de la Société Française d'ORL, 2021, Paris, France (2021)
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Using automatic speech recognition to predict aided speech-in-noise intelligibility
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In: Speech In Noise Workshop ; https://hal.archives-ouvertes.fr/hal-02960442 ; Speech In Noise Workshop, Jan 2020, Toulouse, France ; https://2020.speech-in-noise.eu/?p=program&id=105 (2020)
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Functional impact of speech disorders in patients treated for oral or oropharyngeal cancer, assessed by perceptual and automatic measurements
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In: 2020 Motor Speech Conference ; https://hal.archives-ouvertes.fr/hal-02505380 ; 2020 Motor Speech Conference, Feb 2020, Santa Barbara, United States. ⟨10.13140/RG.2.2.35402.52168⟩ (2020)
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Effects of oral and oropharyngeal cancer on speech intelligibility using acoustic analysis: Systematic review
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In: ISSN: 1043-3074 ; EISSN: 1097-0347 ; Head and Neck ; https://hal.archives-ouvertes.fr/hal-02492761 ; Head and Neck, Wiley, 2020, 42 (1), pp.111-130. ⟨10.1002/hed.25949⟩ (2020)
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A new measure to predict the a priori performance of automatic transcription systems on reverberated speech
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In: Speech In Noise Workshop - SpiN 2019 ; https://hal.archives-ouvertes.fr/hal-02976602 ; Speech In Noise Workshop - SpiN 2019, Jan 2019, Ghent, Belgium ; https://spin2019.be/?p=program&id=86 (2019)
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Abstract:
International audience ; Advances in the field of Automatic Speech Recognition (ASR) make it possible to use this technology in less and less controlled environments. However, reverberation remains a challenge. The purpose of this study is to predict the a priori reverberation impact on the ASR performance. We analysed the statistical behaviour of the vocal excitation of the vowels and created a measure based on this observation. This measure is called Excitation Behaviour (EB). To find the link between the EB and the Word Error Rate (WER) obtained by the transcription system, a regression model was calculated. To evaluate the performance of the regression model we observed the mean prediction error. We also used the same protocol on two other measures: Speech-to-Reverberation Modulation energy Ratio (SRMR) and Spectral Decay Distribution (SDD). The speech corpus used is the Wall Street Journal (WSJ0 and WSJ1) corpus. Speech was artificially reverberated using Room Impulse Response (RIR) from the REVERB challenge corpus. Recorded RIRs allow to simulate 7 different reverberation conditions: 3 rooms with different sizes (Small, Medium and Large) with 2 types of distances between a speaker and a microphone array (near=50cm and far=200 cm), and the last condition is without reverberation. ASR system was trained with the subset trainₛi284, the regression model was trained with dev93 and eval92 was used to test the prediction. It shows that the EB obtains an average prediction error of 13.88 while the SRMR obtains 17.87 and the SDD 17.48. Using 20 utterances (approximately 2m20s), the average prediction error decreases to 7.63 for the EB, 13.08 for the SRMR and 13.02 for the SDD. EB measure is better correlated to ASR performance than other reverberation measures.
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Keyword:
[INFO]Computer Science [cs]
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URL: https://hal.archives-ouvertes.fr/hal-02976602
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| 16 |
The Airbus Air Traffic Control speech recognition 2018 challenge: towards ATC automatic transcription and call sign detection
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In: Proceedings of INTERSPEECH 2019 ; 20th Annual Conference of the International Speech Communication Association (INTERSPEECH 2019) ; https://hal.archives-ouvertes.fr/hal-02419437 ; 20th Annual Conference of the International Speech Communication Association (INTERSPEECH 2019), Sep 2019, Graz, Austria. pp.2993-2997 (2019)
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Interests of using Automatic Speech recognition for Speech-Language Therapists
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In: World Congress of the International Association of Logopedics and Phoniatrics ; https://hal.archives-ouvertes.fr/hal-03012571 ; World Congress of the International Association of Logopedics and Phoniatrics, IALP : International Association of Logopedics and Phoniatrics, Aug 2019, Taipei, Taiwan. pp.(electronic medium) ; http://www.ialptaipei2019.org/ (2019)
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| 18 |
EVOLEX : apport de la reconnaissance vocale pour le diagnostic des dysfonctionnements cognitifs légers
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In: Actes des 8e Journees de Phonetique Clinique ; 8e Journees de Phonetique Clinique (JPC 2019) ; https://hal.archives-ouvertes.fr/hal-02442023 ; 8e Journees de Phonetique Clinique (JPC 2019), May 2019, Mons, Belgique. pp.105-106 (2019)
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Comparaison de systèmes automatiques de reconnaissance grand vocabulaire appliqué à de la parole pathologique
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In: Actes des 8e Journees de Phonetique Clinique ; 8e Journees de Phonetique Clinique (JPC 2019) ; https://hal.archives-ouvertes.fr/hal-02421557 ; 8e Journees de Phonetique Clinique (JPC 2019), May 2019, Mons, Belgique. pp.53-54 (2019)
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Using automatic speech recognition for the prediction of impaired speech identification
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In: 11th Speech in Noise Workshop (SPiN 2019) ; https://hal.archives-ouvertes.fr/hal-02976603 ; 11th Speech in Noise Workshop (SPiN 2019), Jan 2019, Ghent, Belgium ; https://spin2019.be/?p=program&id=88 (2019)
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