Medix-AI/coqui-tts
Medix-AI
/
coqui-tts
mirror of https://github.com/coqui-ai/TTS.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity
coqui-tts/recipes/thorsten_DE
History
Eren Gölge 946afa8197
v0.8.0 (#1810) 
* Fix checkpointing GAN models (#1641)

* checkpoint sae step crash fix

* checkpoint save step crash fix

* Update gan.py

updated requested changes

* crash fix

* Fix the --model_name and --vocoder_name arguments need a <model_type> element (#1469)

Co-authored-by: Eren Gölge <erogol@hotmail.com>

* Fix Publish CI (#1597)

* Try out manylinux

* temporary removal of useless pipeline

* remove check and use only manylinux

* Try --plat-name

* Add install requirements

* Add back other actions

* Add PR trigger

* Remove conditions

* Fix sythax

* Roll back some changes

* Add other python versions

* Add test pypi upload

* Add username

* Add back __token__ as username

* Modify name of entry to testpypi

* Set it to release only

* Fix version checking

* Fix tokenizer for punc only (#1717)

* Remove redundant config field

* Fix SSIM loss

* Separate loss tests

* Fix BCELoss adressing  #1192

* Make style

* Add durations as aux input for VITS (#1694)

* Add durations as aux input for VITS

* Make style

* Fix tts_tests

* Fix test_get_aux_input

* Make lint

* feat: updated recipes and lr fix (#1718)

- updated the recipes activating more losses for more stable training
- re-enabling guided attention loss
- fixed a bug about not the correct lr fetched for logging

* Implement VitsAudioConfig (#1556)

* Implement VitsAudioConfig

* Update VITS LJSpeech recipe

* Update VITS VCTK recipe

* Make style

* Add missing decorator

* Add missing param

* Make style

* Update recipes

* Fix test

* Bug fix

* Exclude tests folder

* Make linter

* Make style

* Fix device allocation

* Fix SSIM loss correction

* Fix aux tests (#1753)

* Set n_jobs to 1 for resample script

* Delete resample test

* Set n_jobs 1 in vad test

* delete vad test

* Revert "Delete resample test"

This reverts commit bb7c8466af.

* Remove tests with resample

* Fix for FloorDiv Function Warning (#1760)

* Fix for Floor Function Warning

Fix for Floor Function Warning

* Adding double quotes to fix formatting

Adding double quotes to fix formatting

* Update glow_tts.py

* Update glow_tts.py

* Fix type in download_vctk.sh (#1739)

typo in comment

* Update decoder.py (#1792)

Minor comment correction.

* Update requirements.txt (#1791)

Support for #1775

* Update README.md (#1776)

Fix typo in different and code sample

* Fix & update WaveRNN vocoder model (#1749)

* Fixes KeyError bug. Adding logging to dashboard.

* Make pep8 compliant

* Make style compliant

* Still fixing style

* Fix rand_segment edge case (input_len == seg_len - 1)

* Update requirements.txt; inflect==5.6 (#1809)

New inflect version (6.0) depends on pydantic which has some issues irrelevant to 🐸 TTS. #1808 
Force inflect==5.6 (pydantic free) install to solve dependency issue.

* Update README.md; download progress bar in CLI. (#1797)

* Update README.md

- minor PR
- added model_info usage guide based on #1623 in README.md .

* "added tqdm bar for model download"

* Update manage.py

* fixed style

* fixed style

* sort imports

* Update wavenet.py (#1796)

* Update wavenet.py

Current version does not use "in_channels" argument. 
In glowTTS, we use normalizing flows and so "input dim" == "ouput dim" (channels and length). So, the existing code just uses hidden_channel sized tensor as input to first layer as well as outputs hidden_channel sized tensor. 
However, since it is a generic implementation, I believe it is better to update it for a more general use.

* "in_channels -> hidden_channels"

* Adjust default to be able to process longer sentences (#1835)

Running `tts --text "$text" --out_path …` with a somewhat longer
sentences in the text will lead to warnings like “Decoder stopped with
max_decoder_steps 500” and the sentences just being cut off in the
resulting WAV file.

This happens quite frequently when feeding longer texts (e.g. a blog
post) to `tts`. It's particular frustrating since the error is not
always obvious in the output. You have to notice that there are missing
parts. This is something other users seem to have run into as well [1].

This patch simply increases the maximum number of steps allowed for the
tacotron decoder to fix this issue, resulting in a smoother default
behavior.

[1] https://github.com/mozilla/TTS/issues/734

* Fix language flags generated by espeak-ng phonemizer (#1801)

* fix language flags generated by espeak-ng phonemizer

* Style

* Updated language flag regex to consider all language codes alike

* fix get_random_embeddings --> get_random_embedding (#1726)

* fix get_random_embeddings --> get_random_embedding

function typo leads to training crash, no such function

* fix typo

get_random_embedding

* Introduce numpy and torch transforms (#1705)

* Refactor audio processing functions

* Add tests for numpy transforms

* Fix imports

* Fix imports2

* Implement bucketed weighted sampling for VITS (#1871)

* Update capacitron_layers.py (#1664)

crashing because of dimension miss match   at line no. 57
[batch, 256] vs [batch , 1, 512]
enc_out = torch.cat([enc_out, speaker_embedding], dim=-1)

* updates to dataset analysis notebooks for compatibility with latest version of TTS (#1853)

* Fix BCE loss issue (#1872)

* Fix BCE loss issue

* Remove import

* Remove deprecated files (#1873)

- samplers.py is moved
- distribute.py is replaces by the 👟Trainer

* Handle when no batch sampler (#1882)

* Fix tune wavegrad (#1844)

* fix imports in tune_wavegrad

* load_config returns Coqpit object instead None

* set action (store true) for flag "--use_cuda"; start to tune if module is running as the main program

* fix var order in the result of batch collating

* make style

* make style with black and isort

* Bump up to v0.8.0

* Add new DE Thorsten models (#1898)

- Tacotron2-DDC
- HifiGAN vocoder

Co-authored-by: manmay nakhashi <manmay.nakhashi@gmail.com>
Co-authored-by: camillem <camillem@users.noreply.github.com>
Co-authored-by: WeberJulian <julian.weber@hotmail.fr>
Co-authored-by: a-froghyar <adamfroghyar@gmail.com>
Co-authored-by: ivan provalov <iprovalo@yahoo.com>
Co-authored-by: Tsai Meng-Ting <sarah13680@gmail.com>
Co-authored-by: p0p4k <rajiv.punmiya@gmail.com>
Co-authored-by: Yuri Pourre <yuripourre@users.noreply.github.com>
Co-authored-by: vanIvan <alfa1211@gmail.com>
Co-authored-by: Lars Kiesow <lkiesow@uos.de>
Co-authored-by: rbaraglia <baraglia.r@live.fr>
Co-authored-by: jchai.me <jreus@users.noreply.github.com>
Co-authored-by: Stanislav Kachnov <42406556+geth-network@users.noreply.github.com>
 		2022-08-22 14:54:38 +02:00
..
align_tts Training recipes for thorsten dataset (#1020) 2022-05-30 12:07:31 +02:00
glow_tts Training recipes for thorsten dataset (#1020) 2022-05-30 12:07:31 +02:00
hifigan Training recipes for thorsten dataset (#1020) 2022-05-30 12:07:31 +02:00
multiband_melgan Training recipes for thorsten dataset (#1020) 2022-05-30 12:07:31 +02:00
speedy_speech v0.8.0 (#1810) 2022-08-22 14:54:38 +02:00
tacotron2-DDC Training recipes for thorsten dataset (#1020) 2022-05-30 12:07:31 +02:00
univnet Training recipes for thorsten dataset (#1020) 2022-05-30 12:07:31 +02:00
vits_tts v0.8.0 (#1810) 2022-08-22 14:54:38 +02:00
wavegrad Training recipes for thorsten dataset (#1020) 2022-05-30 12:07:31 +02:00
wavernn Training recipes for thorsten dataset (#1020) 2022-05-30 12:07:31 +02:00
README.md Training recipes for thorsten dataset (#1020) 2022-05-30 12:07:31 +02:00
download_thorsten_DE.sh Training recipes for thorsten dataset (#1020) 2022-05-30 12:07:31 +02:00

README.md

🐸💬 TTS Thorsten Recipes

For running the recipes you need the Thorsten-Voice dataset.

You can download it manually from the official website or use download_thorsten_de.sh alternatively running any of the train_modelX.pyscripts will download the dataset if not already present.

Then, go to your desired model folder and run the training.

Running Python files. (Choose the desired GPU ID for your run and set ```CUDA_VISIBLE_DEVICES```)
```terminal
CUDA_VISIBLE_DEVICES="0" python train_modelX.py
```

💡 Note that these runs are just templates to help you start training your first model. They are not optimized for the best result. Double-check the configurations and feel free to share your experiments to find better parameters together 💪.