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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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Abstract:
arXiv admin note: text overlap with arXiv:2107.12346 ; This paper presents a sequence-to-sequence voice conversion (S2S-VC) algorithm which allows to preserve some aspects of the source speaker during conversion, typically its prosody, which is useful in many real-life application of voice conversion. In S2S-VC, the decoder is usually conditioned on linguistic and speaker embeddings only, with the consequence that only the linguistic content is actually preserved during conversion. In the proposed S2S-VC architecture, the decoder is conditioned explicitly on the desired F0 sequence so that the converted speech has the same F0 as the one of the source speaker, or any F0 defined arbitrarily. Moreover, an adversarial module is further employed so that the S2S-VC is not only optimized on the available true speech samples, but can also take efficiently advantage of the converted speech samples that can be produced by using various conditioning such as speaker identity, F0, or timing.
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Keyword:
[INFO.INFO-SD]Computer Science [cs]/Sound [cs.SD]; [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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URL: https://hal.archives-ouvertes.fr/hal-03569597
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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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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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