Full metadata record
| DC pole | Hodnota | Jazyk |
|---|---|---|
| dc.contributor.author | Tihelka, Daniel | |
| dc.contributor.author | Matoušek, Jindřich | |
| dc.contributor.author | Tihelková, Alice | |
| dc.date.accessioned | 2022-03-28T10:00:27Z | - |
| dc.date.available | 2022-03-28T10:00:27Z | - |
| dc.date.issued | 2021 | |
| dc.identifier.citation | TIHELKA, D. MATOUŠEK, J. TIHELKOVÁ, A. How Much End-to-End is Tacotron 2 End-to-End TTS System. In Text, Speech, and Dialogue 24th International Conference, TSD 2021, Olomouc, Czech Republic, September 6–9, 2021, Proceedings. Cham: Springer International Publishing, 2021. s. 511-522. ISBN: 978-3-030-83526-2 , ISSN: 0302-9743 | cs |
| dc.identifier.isbn | 978-3-030-83526-2 | |
| dc.identifier.issn | 0302-9743 | |
| dc.identifier.uri | 2-s2.0-85115273150 | |
| dc.identifier.uri | http://hdl.handle.net/11025/47247 | |
| dc.format | 12 s. | cs |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | en | en |
| dc.publisher | Springer International Publishing | en |
| dc.relation.ispartofseries | Text, Speech, and Dialogue 24th International Conference, TSD 2021, Olomouc, Czech Republic, September 6–9, 2021, Proceedings | en |
| dc.rights | Plný text je přístupný v rámci univerzity přihlášeným uživatelům. | cs |
| dc.rights | © Springer | en |
| dc.title | How Much End-to-End is Tacotron 2 End-to-End TTS System | en |
| dc.type | konferenční příspěvek | cs |
| dc.type | ConferenceObject | en |
| dc.rights.access | restrictedAccess | en |
| dc.type.version | publishedVersion | en |
| dc.description.abstract-translated | In recent years, the concept of end-to-end text-to-speech synthesis has begun to attract the attention of researchers. The motivation is simple – replacing the individual modules that TTS traditionally built on with a powerful deep neural network simplifies the architecture of the entire system. However, how capable are such end-to-end systems of dealing with classic tasks such as G2P, text normalisation, homograph disambiguation and other issues inseparably linked to text-to-speech systems? In the present paper, we explore three free implementations of the Tacotron 2-based speech synthesizers, focusing on their abilities to transform the input text into correct pronunciation, not only in terms of G2P conversion but also in han- dling issues related to text analysis and the prosody patterns used. | en |
| dc.subject.translated | End-to-end speech synthesis | en |
| dc.subject.translated | Tacotron 2 | en |
| dc.subject.translated | WaveRNN | en |
| dc.subject.translated | MelGan | en |
| dc.subject.translated | Text processing | en |
| dc.subject.translated | Homograph disambiguation | en |
| dc.subject.translated | Prosody patterns | en |
| dc.identifier.doi | 10.1007/978-3-030-83527-9_44 | |
| dc.type.status | Peer-reviewed | en |
| dc.identifier.obd | 43933411 | |
| dc.project.ID | GA19-19324S/Plně trénovatelná syntéza české řeči z textu s využitím hlubokých neuronových sítí | cs |
| dc.project.ID | 90140/Velká výzkumná infrastruktura_(J) - e-INFRA CZ | cs |
| Vyskytuje se v kolekcích: | Konferenční příspěvky / Conference papers (KAJ) Konferenční příspěvky / Conference Papers (KKY) OBD | |
Soubory připojené k záznamu:
| Soubor | Velikost | Formát | |
|---|---|---|---|
| Tihelka2021_Chapter_HowMuchEnd-to-EndIsTacotron2En.pdf | 222,38 kB | Adobe PDF | Zobrazit/otevřít Vyžádat kopii |
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