Medix-AI/coqui-tts
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coqui-tts
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Edresson Casanova 8d228ab22a
Trick to Upsampling to High sampling rates using VITS model (#1456) 
* Add upsample VITS support

* Fix the bug in inference

* Fix lint checks

* Add RMS based norm in save_wav method

* Style fix

* Add the period for VITS multi-period discriminator in model_args

* Bug fix in speaker encoder load in inference time

* Add unit tests

* Remove useless detach_z_vocoder parameter

* Add docs for VITS upsampling

* Fix the docs

* Rename TTS_part_sample_rate to encoder_sample_rate

* Add upsampling_init and upsampling_z methods

* Add asserts for encoder_sample_rate part

* Move upsampling tests to test_vits.py
 		2022-04-26 11:47:46 +02:00
..
static Merge branch 'dev' of https://github.com/coqui-ai/TTS into dev 2021-03-08 15:21:06 +01:00
templates small refactor in server.py 2021-04-23 18:04:37 +02:00
README.md Update model file extension (#1422) 2022-03-22 17:55:00 +01:00
__init__.py rename the project to old TTS 2020-09-09 12:27:23 +02:00
conf.json Update model file extension (#1422) 2022-03-22 17:55:00 +01:00
server.py Trick to Upsampling to High sampling rates using VITS model (#1456) 2022-04-26 11:47:46 +02:00

README.md

🐸 TTS demo server

Before you use the server, make sure you install) 🐸 TTS properly. Then, you can follow the steps below.

Note: If you install 🐸TTS using pip, you can also use the tts-server end point on the terminal.

Examples runs:

List officially released models. python TTS/server/server.py --list_models

Run the server with the official models. python TTS/server/server.py --model_name tts_models/en/ljspeech/tacotron2-DCA --vocoder_name vocoder_models/en/ljspeech/multiband-melgan

Run the server with the official models on a GPU. CUDA_VISIBLE_DEVICES="0" python TTS/server/server.py --model_name tts_models/en/ljspeech/tacotron2-DCA --vocoder_name vocoder_models/en/ljspeech/multiband-melgan --use_cuda True

Run the server with a custom models. python TTS/server/server.py --tts_checkpoint /path/to/tts/model.pth --tts_config /path/to/tts/config.json --vocoder_checkpoint /path/to/vocoder/model.pth --vocoder_config /path/to/vocoder/config.json