mirror of https://github.com/coqui-ai/TTS.git
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MOS Results
Eren Gölge edited this page 2021-03-05 18:21:18 +01:00
Based on our latest MOS study, 🐸 TTS is able to achieve on par performance with any other solution. However, it is also shown that the quality of the dataset is an important part of 🐸 TTS. Therefore, it is worth to find a good resource or even record your own dataset, if you like to peak the 🐸 TTS performance.
Models
- Judy Wave1: Tacotron + WaveRNN
- Judy Wave2: Tacotron2 + WaveRNN
- Judy GL1 : Tacotron + Griffin Lim
- Judy GL2 : Tacotron2 + Griffin Lim
- TTS Nancy: Tacotron + Griffin Lim
- TTS Nancy2: Tacotron2 + WaveRNN
- TTS LJSpeech: Tacotron + GriffinLim
(Judy is an 25 hours long internal dataset)
(.Jofish .Abe and .Janice are real human voices)
