تقرير
Speaker Generation
| العنوان: | Speaker Generation |
|---|---|
| المؤلفون: | Stanton, Daisy, Shannon, Matt, Mariooryad, Soroosh, Skerry-Ryan, RJ, Battenberg, Eric, Bagby, Tom, Kao, David |
| سنة النشر: | 2021 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Sound, Computer Science - Computation and Language, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Audio and Speech Processing, I.2.7, G.3 |
| الوصف: | This work explores the task of synthesizing speech in nonexistent human-sounding voices. We call this task "speaker generation", and present TacoSpawn, a system that performs competitively at this task. TacoSpawn is a recurrent attention-based text-to-speech model that learns a distribution over a speaker embedding space, which enables sampling of novel and diverse speakers. Our method is easy to implement, and does not require transfer learning from speaker ID systems. We present objective and subjective metrics for evaluating performance on this task, and demonstrate that our proposed objective metrics correlate with human perception of speaker similarity. Audio samples are available on our demo page. Comment: 12 pages, 3 figures, 4 tables, appendix with 2 tables |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2111.05095 |
| رقم الأكسشن: | edsarx.2111.05095 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |