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Об истории речевых исследований в России ... : About the history of speech research in Russia ...
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Implementing a Statistical Parametric Speech Synthesis System for a Patient with Laryngeal Cancer
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In: Sensors; Volume 22; Issue 9; Pages: 3188 (2022)
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Evaluation of Tacotron Based Synthesizers for Spanish and Basque
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In: Applied Sciences; Volume 12; Issue 3; Pages: 1686 (2022)
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Contribution of Vocal Tract and Glottal Source Spectral Cues in the Generation of Acted Happy and Aggressive Spanish Vowels
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In: Applied Sciences; Volume 12; Issue 4; Pages: 2055 (2022)
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Neural Vocoding for Singing and Speaking Voices with the Multi-Band Excited WaveNet
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In: Information; Volume 13; Issue 3; Pages: 103 (2022)
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Abstract:
The use of the mel spectrogram as a signal parameterization for voice generation is quite recent and linked to the development of neural vocoders. These are deep neural networks that allow reconstructing high-quality speech from a given mel spectrogram. While initially developed for speech synthesis, now neural vocoders have also been studied in the context of voice attribute manipulation, opening new means for voice processing in audio production. However, to be able to apply neural vocoders in real-world applications, two problems need to be addressed: (1) To support use in professional audio workstations, the computational complexity should be small, (2) the vocoder needs to support a large variety of speakers, differences in voice qualities, and a wide range of intensities potentially encountered during audio production. In this context, the present study will provide a detailed description of the Multi-band Excited WaveNet, a fully convolutional neural vocoder built around signal processing blocks. It will evaluate the performance of the vocoder when trained on a variety of multi-speaker and multi-singer databases, including an experimental evaluation of the neural vocoder trained on speech and singing voices. Addressing the problem of intensity variation, the study will introduce a new adaptive signal normalization scheme that allows for robust compensation for dynamic and static gain variations. Evaluations are performed using objective measures and a number of perceptual tests including different neural vocoder algorithms known from the literature. The results confirm that the proposed vocoder compares favorably to the state-of-the-art in its capacity to generalize to unseen voices and voice qualities. The remaining challenges will be discussed.
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Keyword:
adversarial training; mel spectrogram; neural vocoder; singing synthesis; singing transformation; speech synthesis; speech transformation
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URL: https://doi.org/10.3390/info13030103
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Affect Expression: Global and Local Control of Voice Source Parameters ; Speech Prosody
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Prosodic Boundary Prediction Model for Vietnamese Text-To-Speech
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In: Proc. Interspeech 2021 ; Interspeech 2021 ; https://hal.archives-ouvertes.fr/hal-03329116 ; Interspeech 2021, Aug 2021, Brno, Czech Republic. pp.3885-3889, ⟨10.21437/interspeech.2021-125⟩ (2021)
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Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03332224 ; 2021 (2021)
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Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03332224 ; 2021 (2021)
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Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03332224 ; 2021 (2021)
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Impact of Segmentation and Annotation in French end-to-end Synthesis
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In: Proc. 11th ISCA Speech Synthesis Workshop (SSW 11) ; SSW 11th ISCA Speech Synthesis Workshop ; https://hal.archives-ouvertes.fr/hal-03362000 ; SSW 11th ISCA Speech Synthesis Workshop, Aug 2021, Budapest, Hungary. pp.13-18, ⟨10.21437/SSW.2021-3⟩ ; https://ssw11.hte.hu/ (2021)
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Anonymous speaker clusters: Making distinctions between anonymised speech recordings with clustering interface
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In: INTERSPEECH 2021 ; https://hal.archives-ouvertes.fr/hal-03267084 ; INTERSPEECH 2021, Aug 2021, Brno, Czech Republic (2021)
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Learning emotions latent representation with CVAE for Text-Driven Expressive AudioVisual Speech Synthesis
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In: ISSN: 0893-6080 ; Neural Networks ; https://hal.inria.fr/hal-03204193 ; Neural Networks, Elsevier, 2021, 141, pp.315-329. ⟨10.1016/j.neunet.2021.04.021⟩ (2021)
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