Name
Abstract | ||
|---|---|---|
Statistical TTS systems that directly predict the speech waveform have recently reported improvements in synthesis quality. This investigation evaluates Amazon’s statistical speech waveform synthesis (SSWS) system. An in-depth evaluation of SSWS is conducted across a number of domains to better understand the consistency in quality. The results of this evaluation are validated by repeating the procedure on a separate group of testers. Finally, an analysis of the nature of speech errors of SSWS compared to hybrid unit selection synthesis is conducted to identify the strengths and weaknesses of SSWS. Having a deeper insight into SSWS allows us to better define the focus of future work to improve this new technology. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/slt.2018.8639556 | 2018 IEEE Spoken Language Technology Workshop (SLT) |
Keywords | DocType | Volume |
Speech synthesis,Vocoders,Testing,Transforms,Training,Production,Predictive models | Conference | abs/1811.06296 |
ISSN | Citations | PageRank |
2639-5479 | 0 | 0.34 |
References | Authors | |
11 | 13 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Thomas Merritt | 1 | 18 | 5.81 |
| Bartosz Putrycz | 2 | 0 | 0.34 |
| Adam Nadolski | 3 | 0 | 0.34 |
| Tianjun Ye | 4 | 0 | 0.34 |
| Daniel Korzekwa | 5 | 2 | 3.10 |
| Wiktor Dolecki | 6 | 0 | 0.34 |
| Thomas Drugman | 7 | 526 | 41.79 |
| Viacheslav Klimkov | 8 | 5 | 3.19 |
| Alexis Moinet | 9 | 103 | 13.48 |
| Andrew Breen | 10 | 0 | 0.34 |
| Rafal Kuklinski | 11 | 0 | 0.34 |
| Nikko Strom | 12 | 84 | 6.93 |
| Roberto Barra-Chicote | 13 | 129 | 17.35 |