An overview & analysis of sequence-to-sequence emotional voice conversion

  • Emotional voice conversion (EVC) focuses on converting a speech utterance from a source to a target emotion; it can thus be a key enabling technology for human-computer interaction applications and beyond. However, EVC remains an unsolved research problem with several challenges. In particular, as speech rate and rhythm are two key factors of emotional conversion, models have to generate output sequences of differing length. Sequence-to-sequence modelling is recently emerging as a competitive paradigm for models that can overcome those challenges. In an attempt to stimulate further research in this promising new direction, recent sequence-to-sequence EVC papers were systematically investigated and reviewed from six perspectives: their motivation, training strategies, model architectures, datasets, model inputs, and evaluation methods. This information is organised to provide the research community with an easily digestible overview of the current state-of-the-art. Finally, we discussEmotional voice conversion (EVC) focuses on converting a speech utterance from a source to a target emotion; it can thus be a key enabling technology for human-computer interaction applications and beyond. However, EVC remains an unsolved research problem with several challenges. In particular, as speech rate and rhythm are two key factors of emotional conversion, models have to generate output sequences of differing length. Sequence-to-sequence modelling is recently emerging as a competitive paradigm for models that can overcome those challenges. In an attempt to stimulate further research in this promising new direction, recent sequence-to-sequence EVC papers were systematically investigated and reviewed from six perspectives: their motivation, training strategies, model architectures, datasets, model inputs, and evaluation methods. This information is organised to provide the research community with an easily digestible overview of the current state-of-the-art. Finally, we discuss existing challenges of sequence-to-sequence EVC.show moreshow less

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Metadaten
Author:Zijiang Yang, Xin Jing, Andreas TriantafyllopoulosORCiD, Meishu Song, Ilhan AslanORCiDGND, Björn W. SchullerORCiDGND
URN:urn:nbn:de:bvb:384-opus4-992886
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/99288
Parent Title (English):Interspeech 2022, Incheon, Korea, 18-22 September 2022
Publisher:ISCA
Place of publication:Baixas
Editor:Hanseok Ko, John H. L. Hansen
Type:Conference Proceeding
Language:English
Year of first Publication:2022
Publishing Institution:Universität Augsburg
Release Date:2022/11/15
First Page:4915
Last Page:4919
DOI:https://doi.org/10.21437/interspeech.2022-10636
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Embedded Intelligence for Health Care and Wellbeing
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):Deutsches Urheberrecht