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Speaker Attentive Speech Emotion Recognition
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In: Proccedings of interspeech 2021 ; Interspeech 2021 ; https://hal.archives-ouvertes.fr/hal-03554368 ; Interspeech 2021, Aug 2021, Brno, Czech Republic. pp.2866-2870, ⟨10.21437/interspeech.2021-573⟩ (2021)
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Sequence-To-Sequence Voice Conversion using F0 and Time Conditioning and Adversarial Learning
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In: https://hal.archives-ouvertes.fr/hal-03569597 ; 2021 (2021)
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Beyond Voice Identity Conversion: Manipulating Voice Attributes by Adversarial Learning of Structured Disentangled Representations
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In: https://hal.archives-ouvertes.fr/hal-03569608 ; 2021 (2021)
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Beyond Voice Identity Conversion: Manipulating Voice Attributes by Adversarial Learning of Structured Disentangled Representations ...
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Sequence-To-Sequence Voice Conversion using F0 and Time Conditioning and Adversarial Learning ...
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Att-HACK: An Expressive Speech Database with Social Attitudes
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In: Speech Prosody ; https://hal.archives-ouvertes.fr/hal-02508362 ; Speech Prosody, May 2020, Tokyo, Japan (2020)
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SEQUENCE-TO-SEQUENCE MODELLING OF F0 FOR SPEECH EMOTION CONVERSION
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In: IEEE International Conference on Acoustics, Speech, and Signal Processing ; https://hal.sorbonne-universite.fr/hal-02018439 ; IEEE International Conference on Acoustics, Speech, and Signal Processing, May 2019, Brighton, United Kingdom (2019)
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« The annotation of syllabic prominences and disfluencies »
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In: Rhapsodie: A prosodic and syntactic treebank for spoken French. Amsterdam: Benjamins, ; https://hal.archives-ouvertes.fr/hal-03324669 ; in Lacheret, A., Kahane, S. & Pietrandrea, P. (eds). Rhapsodie: A prosodic and syntactic treebank for spoken French. Amsterdam: Benjamins,, pp.157-173, 2019 (2019)
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AUTOMATIC MODELLING AND LABELLING OF SPEECH PROSODY: WHAT'S NEW WITH SLAM+ ?
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In: International Congress of Phonetic Sciences (ICPhS) ; https://hal.sorbonne-universite.fr/hal-02119926 ; International Congress of Phonetic Sciences (ICPhS), Aug 2019, Melbourne, Australia (2019)
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At the Interface of Speech and Music: A Study of Prosody and Musical Prosody in Rap Music
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In: Speech Prosody ; https://hal.sorbonne-universite.fr/hal-01722009 ; Speech Prosody, Jun 2018, Poznan, Poland (2018)
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Score-Informed Syllable Segmentation for Jingju a Cappella Singing Voice with Mel-Frequency Intensity Profiles
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In: International Workshop on Folk Music Analysis ; https://hal.sorbonne-universite.fr/hal-01513160 ; International Workshop on Folk Music Analysis, Jun 2017, Malaga, Spain (2017)
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Score-Informed Syllable Segmentation For Jingju A Cappella Singing Voice With Mel-Frequency Intensity Profiles ...
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Score-Informed Syllable Segmentation For Jingju A Cappella Singing Voice With Mel-Frequency Intensity Profiles ...
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Score-Informed Syllable Segmentation For Jingju A Cappella Singing Voice With Mel-Frequency Intensity Profiles ...
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Vers une modélisation continue de la structure prosodique: le cas des proéminences syllabiques
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Abstract:
L'objectif de cet article est de présenter un outil développé en vue de modéliser semi-automatiquement la structure prosodique du français. Sur la base d'un alignement en phonèmes, notre système procède à la détection des syllabes proéminentes en prenant en considération des critères acoustiques basiques tels que la f0, la durée et la présence de pauses. À partir des mesures ainsi prises, le système attribue un degré de proéminence à chacune des syllabes identifiées comme saillante. Nous illustrons ensuite les résultats de l'analyse d'extraits du corpus PROSO_FR. Plus précisément, nous comparons l'analyse prosodique de phrases que l'on pourrait faire avec les règles traditionnelles de la phonologie prosodique avec l'analyse conduite par notre logiciel. Nous discutons ainsi de trois règles: la règle de dominance droite, la règle de clash accentuel et la règle des sept syllabes
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URL: http://doc.rero.ch/record/294263/files/S0959269510000517.pdf
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A Source/Filter Model with Adaptive Constraints for NMF-based Speech Separation
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In: International Conference on Acoustics, Speech, and Signal Processing ; https://hal.sorbonne-universite.fr/hal-01294681 ; International Conference on Acoustics, Speech, and Signal Processing, Mar 2016, Shanghai, China (2016)
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Similarity Search of Acted Voices for Automatic Voice Casting
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In: ISSN: 2329-9290 ; EISSN: 2329-9304 ; IEEE/ACM Transactions on Audio, Speech and Language Processing ; https://hal.sorbonne-universite.fr/hal-01464715 ; IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2016, 24 (9), pp.1642 - 1651. ⟨10.1109/TASLP.2016.2580302⟩ (2016)
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Symbolic Modeling of Prosody: From Linguistics to Statistics
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In: ISSN: 1558-7916 ; IEEE Transactions on Audio, Speech and Language Processing ; https://hal.archives-ouvertes.fr/hal-01164602 ; IEEE Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2015, 23 (3), pp.588 - 599. ⟨10.1109/TASLP.2014.2387389⟩ (2015)
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Exploiting Alternatives for Text-To-Speech Synthesis: From Machine to Human
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In: Speech Prosody in Speech Synthesis: Modeling and Generation of Prosody for High Quality and Flexible Speech Synthesis ; https://hal.archives-ouvertes.fr/hal-01164642 ; Springer Berlin Heidelberg. Speech Prosody in Speech Synthesis: Modeling and Generation of Prosody for High Quality and Flexible Speech Synthesis, pp.189-202, 2015, Prosody, Phonology and Phonetics, 978-3-662-45258-5. ⟨10.1007/978-3-662-45258-5_13⟩ (2015)
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The Role of Glottal Source Parameters for High-Quality Transformation of Perceptual Age
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In: International Conference on Acoustics, Speech, and Signal Processing (ICASSP) ; https://hal.archives-ouvertes.fr/hal-01164562 ; International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Apr 2015, Brisbane, Australia (2015)
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