| Title: | Text-to-Text Transfer Transformer Phrasing Model Using Enriched Text Input |
| Authors: | Řezáčková, Markéta Matoušek, Jindřich |
| Citation: | ŘEZÁČKOVÁ, M. MATOUŠEK, J. Text-to-Text Transfer Transformer Phrasing Model Using Enriched Text Input. In Text, Speech, and Dialogue 25th International Conference, TSD 2022, Brno, Czech Republic, September 6–9, 2022, Proceedings. Cham: Springer International Publishing, 2022. s. 389-400. ISBN: 978-3-031-16269-5 , ISSN: 0302-9743 |
| Issue Date: | 2022 |
| Publisher: | Springer International Publishing |
| Document type: | konferenční příspěvek ConferenceObject |
| URI: | 2-s2.0-85139025870 http://hdl.handle.net/11025/50926 |
| ISBN: | 978-3-031-16269-5 |
| ISSN: | 0302-9743 |
| Keywords in different language: | Phrasing;Prosodic boundaries;T5;Part-of-Speech tags;Syntactic categories |
| Abstract in different language: | Appropriate prosodic phrasing of the input text is crucial for natural speech synthesis outputs. The presented paper focuses on using a Text-to-Text Transfer Transformer for predicting phrase boundaries in text and inspects the possibility of enriching the input text with more detailed information to improve the success rate of the phrasing model trained on plain text. This idea came from our previous research on phrasing that showed that more detailed syntactic/semantic information might lead to more accurate predicting of phrase boundaries. |
| Rights: | Plný text je přístupný v rámci univerzity přihlášeným uživatelům. © Springer Nature Switzerland AG |
| Appears in Collections: | Konferenční příspěvky / Conference papers (NTIS) Konferenční příspěvky / Conference Papers (KKY) OBD |
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| Rezackova_Matousek-Text-to-Text_Transfer_TSD_2022.pdf | 260,95 kB | Adobe PDF | View/Open Request a copy |
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