[New model] 🐸TTS advanced Text-to-Speech
### Model description

🐸TTS is a library for advanced Text-to-Speech generation. It's built on the latest research, was designed to achieve the best trade-off among ease-of-training, speed and quality. 🐸TTS comes with pretrained models, tools for measuring dataset quality and already used in 20+ languages for products and research projects.

### Open source status

- [X] The model implementation is available
- [X] The model weights are available

### Provide useful links for the implementation

GithHub repo: https://github.com/coqui-ai/TTS
Samples: http://erogol.com/ddc-samples/
Hi @jozefchutka I would like to work on this issue, I see multiple models under [Implemented Models](https://github.com/coqui-ai/TTS/tree/dev#implemented-models) on your link, do you have any recommendation about which one to start first?<|||||>Hi @susnato , thanks for looking into this. I hope to eventually run TTS in browser via (transformers.js), based on which my recommendation would be to pick a model that would be suitable in terms of performance / size<|||||>Hi @jozefchutka thanks for replying, I was thinking about Speedy-Speech but I didn't see that model inside of `TTS/tts/models` in dev branch, am I looking in wrong branch?<|||||>I have no idea honestly. But I have just discovered github provides very nice code browsing view, including search.
![Clipboard01](https://github.com/huggingface/transformers/assets/750041/fd4854a7-cc0a-4e9e-b87b-92bc079ff41c)

If its nowhere to find, it would be worth to reach out to 🐸TTS team
<|||||>cc @sanchit-gandhi <|||||>Hey @jozefchutka and @susnato - Coqui were previously focused on providing strong open-source TTS checkpoints, however in the last year they pivoted to more end-user services (see https://twitter.com/coqui_ai/status/1638573847296499712). They haven't been open-sourcing these latest models, and as a result their open-source checkpoints have fallen by the wayside a bit compared to the latest TTS research (e.g. VALL-E, Bark, MQTTS). I would say that a year ago it would have been a very exciting addition, but now there are more performant checkpoints that are growing in popularity amongst the open-source community. I would recommend checking out the aforementioned models if you're interested in a TTS model integration! Also see related https://github.com/huggingface/transformers/issues/22487#issuecomment-1496340245<|||||>Hi @sanchit-gandhi thanks for replying! Actually I was going through the same issue and saw your [comment](https://github.com/huggingface/transformers/issues/22487#issuecomment-1496312713) -

>Indeed, a TTS pipeline would be super helpful to run SpeechT5. We're currently planning on waiting till we have 1-2 more TTS models in the library before pushing ahead with a TTS pipeline, in order to verify that the pipeline is generalisable and gives a benefit over loading a single model + processor.

I was hoping to somehow contribute to the TTS pipeline, but now that you said  
>They haven't been open-sourcing these latest models, and as a result their open-source checkpoints have fallen by the wayside a bit compared to the latest TTS research (e.g. VALL-E, Bark, MQTTS)

is a TTS pipeiline still in queue or should I focus on others like https://paperswithcode.com/task/text-to-speech-synthesis ?



<|||||>Hi @sanchit-gandhi @susnato thanks for the insights. If there are better alternatives please go for it. <|||||>IMO the TTS pipeline will be worth pursuing once the two ongoing TTS PRs are complete:
* Bark #23375
* FastSpeech2 #23439 

=> we'd then have three models on which to base the TTS pipeline!

Right now I think these are probably the most worthwhile TTS models to work on in transformers? There's also MQTTS: https://github.com/b04901014/MQTTS But that hasn't gained much traction. Do you know of any other recent TTS models that are gaining popularity amongst the community that we might have missed?<|||||>The only other bookmark I have is https://github.com/elevenlabs/elevenlabs-python , but that doesnt seem open model, just API? Worth for someone with better understanding in field to research.<|||||>As far as I understand, ElevenLabs is only a paid API @jozefchutka, but definitely a performant low-latency model. Interestingly a new ElevenLabs demo popped-up on the HF Hub: https://huggingface.co/spaces/elevenlabs/tts So potentially they're trying to increase their OS presence?<|||||>My understanding is the same<|||||>Hi  @sanchit-gandhi my knowledge about recent TTS models is very limited, but I read about some of them maybe they are worth adding - how  about [Tacotron 2](https://arxiv.org/pdf/1712.05884.pdf)(an implementation by NVIDIA [here](https://github.com/NVIDIA/tacotron2)) or [Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling](https://arxiv.org/pdf/2103.14574.pdf) . Also I found some unofficial implementations for [VALL-E](https://arxiv.org/pdf/2301.02111.pdf) - [lifeiteng/vall-e](https://github.com/lifeiteng/vall-e/tree/main) and [enhuiz/vall-e](https://github.com/enhuiz/vall-e) but both are without pretrained weights or [TransformerTTS](https://arxiv.org/pdf/1809.08895.pdf) (an PaddlePaddle implementation [here](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/paddlespeech/t2s/models/transformer_tts/transformer_tts.py) and weights [here](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/ljspeech/tts1)). 

If  they are not as interesting then I would like to implement MQTTS. What do you think?