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Evaluation of Speaker Anonymization on Emotional Speech ; Analyse de l'anonymisation du locuteur sur de la parole émotionnelle
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In: JEP2022 - Journées d'Études sur la Parole ; https://hal.archives-ouvertes.fr/hal-03636737 ; JEP2022 - Journées d'Études sur la Parole, Jun 2022, Île de Noirmoutier, France (2022)
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On the use of Self-supervised Pre-trained Acoustic and Linguistic Features for Continuous Speech Emotion Recognition
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In: IEEE Spoken Language Technology Workshop ; https://hal.archives-ouvertes.fr/hal-03003469 ; IEEE Spoken Language Technology Workshop, Jan 2021, Virtual, China (2021)
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Evaluation of Speaker Anonymization on Emotional Speech
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In: 1st ISCA Symposium on Security and Privacy in Speech Communication ; https://hal.inria.fr/hal-03377797 ; 1st ISCA Symposium on Security and Privacy in Speech Communication, Nov 2021, Virtual, Germany (2021)
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Towards Interactive Annotation for Hesitation in Conversational Speech
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In: LREC 2020 ; https://hal.archives-ouvertes.fr/hal-02505333 ; LREC 2020, May 2020, Marseille, France (2020)
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Can we Generate Emotional Pronunciations for Expressive Speech Synthesis?
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In: ISSN: 1949-3045 ; IEEE Transactions on Affective Computing ; https://hal.archives-ouvertes.fr/hal-01802463 ; IEEE Transactions on Affective Computing, Institute of Electrical and Electronics Engineers, 2020, 11 (4), pp.684-695. ⟨10.1109/TAFFC.2018.2828429⟩ (2020)
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On the use of Self-supervised Pre-trained Acoustic and Linguistic Features for Continuous Speech Emotion Recognition ...
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SynPaFlex-Corpus: An Expressive French Audiobooks Corpus Dedicated to Expressive Speech Synthesis
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In: Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018) ; https://hal.archives-ouvertes.fr/hal-01826690 ; Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), May 2018, Miyazaki, Japan ; http://lrec2018.lrec-conf.org/en/ (2018)
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Abstract:
International audience ; This paper presents an expressive French audiobooks corpus containing eighty seven hours of good audio quality speech, recorded by a single amateur speaker reading audiobooks of different literary genres. This corpus departs from existing corpora collected from audiobooks since they usually provide a few hours of mono-genre and multi-speaker speech. The motivation for setting up such a corpus is to explore expressiveness from different perspectives, such as discourse styles, prosody, and pronunciation, and using different levels of analysis (syllable, prosodic and lexical words, prosodic and syntactic phrases, utterance or paragraph). This will allow developing models to better control expressiveness in speech synthesis, and to adapt pronunciation and prosody to specific discourse settings (changes in discourse perspectives, indirect vs. direct styles, etc.). To this end, the corpus has been annotated automatically and provides information as phone labels, phone boundaries, syllables, words or morpho-syntactic tagging. Moreover, a significant part of the corpus has also been annotated manually to encode direct/indirect speech information and emotional content. The corpus is already usable for studies on prosody and TTS purposes and is available to the community.
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Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO]Computer Science [cs]; Prosody; Speech Resource/Database; Speech Synthesis
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URL: https://hal.archives-ouvertes.fr/hal-01826690/document
https://hal.archives-ouvertes.fr/hal-01826690
https://hal.archives-ouvertes.fr/hal-01826690/file/723.pdf
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Discourse phrases classification: direct vs. narrative audio speech
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In: Speech Prosody ; https://hal.archives-ouvertes.fr/hal-01790910 ; Speech Prosody, Jun 2018, Poznan, Poland (2018)
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The IRISA Text-To-Speech System for the Blizzard Challenge 2017
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In: Blizzard Challenge ; https://hal.inria.fr/hal-01662361 ; Blizzard Challenge, Aug 2017, Stockholm, Sweden (2017)
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Perception of expressivity in TTS: linguistics, phonetics or prosody?
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In: Statistical Language and Speech Processing ; https://hal-univ-lemans.archives-ouvertes.fr/hal-01623916 ; Statistical Language and Speech Processing, Oct 2017, Le Mans, France. pp.262-274, ⟨10.1007/978-3-319-68456-7_22⟩ ; http://grammars.grlmc.com/SLSP2017/index.php (2017)
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Statistical Pronunciation Adaptation for Spontaneous Speech Synthesis
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In: Text, Speech and Dialogue (TSD) ; https://hal.inria.fr/hal-01532035 ; Text, Speech and Dialogue (TSD), Aug 2017, Prague, Czech Republic (2017)
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Optimal feature set and minimal training size for pronunciation adaptation in TTS
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In: International Conference on Statistical Language and Speech Processing (SLSP) ; https://hal.inria.fr/hal-01338853 ; International Conference on Statistical Language and Speech Processing (SLSP), Oct 2016, Pilsen, Czech Republic (2016)
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Improving TTS with corpus-specific pronunciation adaptation
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In: Interspeech ; https://hal.inria.fr/hal-01338111 ; Interspeech, Sep 2016, San Francisco, United States (2016)
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Corpus of Children Voices for Mid-level Markers and Affect Bursts Analysis
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In: Language Ressource and Evaluation Conference (LREC) ; https://hal.archives-ouvertes.fr/hal-01768827 ; Language Ressource and Evaluation Conference (LREC), 2012, Istanbul, Turkey (2012)
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Acoustic measures characterizing anger across corpora collected in artificial or natural context
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In: Speech Prosody ; https://hal.archives-ouvertes.fr/hal-01768783 ; Speech Prosody, 2010, Chicago, United States (2010)
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