Advanced Speaker Embedding with Predictive Variance of Gaussian Distribution for Speaker Adaptation in TTS
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Jaeuk | - |
dc.contributor.author | Chang, Joon-Hyuk | - |
dc.date.accessioned | 2022-12-20T06:24:39Z | - |
dc.date.available | 2022-12-20T06:24:39Z | - |
dc.date.created | 2022-11-02 | - |
dc.date.issued | 2022-09 | - |
dc.identifier.issn | 2308-457X | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/173083 | - |
dc.description.abstract | Speaker adaptation in text-to-speech (TTS) has three goals: high-quality audio, requirement of a small amount of data for adapting to a new speaker, and fine-tuning few parameters for storage efficiency in commercial service of custom voice. In this paper, we introduce a novel adaptation method to achieve the aforementioned three goals. First, we estimate variances from a speaker embedding and add them back to the speaker embedding. Through this operation, the distribution of each speaker in latent space increases. Moreover, we design a prediction model that could generate a speaker embedding that approximately represents the new speaker's timbre. We can obtain a new speaker embedding well representing the timbre of a new speaker by the search process to the starting point of fine-tuning and the prediction model. We observe the performance change according to the number of fine-tuning parameters. Finally, we evaluate the proposed method using the mean opinion score (MOS) to demonstrate the remarkable performance of our proposed method. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | International Speech Communication Association | - |
dc.title | Advanced Speaker Embedding with Predictive Variance of Gaussian Distribution for Speaker Adaptation in TTS | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Chang, Joon-Hyuk | - |
dc.identifier.doi | 10.21437/Interspeech.2022-10193 | - |
dc.identifier.scopusid | 2-s2.0-85140064816 | - |
dc.identifier.wosid | 000900724503032 | - |
dc.identifier.bibliographicCitation | Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, v.2022-September, pp.2988 - 2992 | - |
dc.relation.isPartOf | Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH | - |
dc.citation.title | Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH | - |
dc.citation.volume | 2022-September | - |
dc.citation.startPage | 2988 | - |
dc.citation.endPage | 2992 | - |
dc.type.rims | ART | - |
dc.type.docType | Proceedings Paper | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Acoustics | - |
dc.relation.journalResearchArea | Audiology & Speech-Language Pathology | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Acoustics | - |
dc.relation.journalWebOfScienceCategory | Audiology & Speech-Language Pathology | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.subject.keywordPlus | Digital storage | - |
dc.subject.keywordPlus | Speech communication | - |
dc.subject.keywordPlus | Embeddings | - |
dc.subject.keywordPlus | Embeddings | - |
dc.subject.keywordPlus | Fine tuning | - |
dc.subject.keywordPlus | High-quality audio | - |
dc.subject.keywordPlus | Multi-speaker | - |
dc.subject.keywordPlus | Performance | - |
dc.subject.keywordPlus | Prediction modelling | - |
dc.subject.keywordPlus | Speaker adaptation | - |
dc.subject.keywordPlus | Storage efficiency | - |
dc.subject.keywordPlus | Text to speech | - |
dc.subject.keywordPlus | Voice cloning | - |
dc.subject.keywordAuthor | multi-speaker | - |
dc.subject.keywordAuthor | speaker adaptation | - |
dc.subject.keywordAuthor | voice cloning | - |
dc.identifier.url | https://www.isca-speech.org/archive/interspeech_2022/lee22j_interspeech.html | - |
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