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Code Issues Packages Projects Releases Wiki Activity

Inference API for 🐶Bark (#2685)

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* Add bark requirements

* Draft Bark implementation

* Download HF models

* Update synthesizer

* Add bark model

* Make style

* Update pylintrc

* Update model URLs

* Update Bark Config

* Fix here and ther

* Make style

* Make lint

* Update requirements

* Update requirements
This commit is contained in:
Eren Gölge
2023-06-28 11:55:27 +02:00
committed by GitHub
parent 4cf8652392
commit c844b6570a
18 changed files with 1757 additions and 101 deletions
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docs/source/models/tortoise.md
+12 -12
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@@ -1,7 +1,7 @@
# Tortoise 🐢
Tortoise is a very expressive TTS system with impressive voice cloning capabilities. It is based on an GPT like autogressive acoustic model that converts input
text to discritized acouistic tokens, a diffusion model that converts these tokens to melspeectrogram frames and a Univnet vocoder to convert the spectrograms to
the final audio signal. The important downside is that Tortoise is very slow compared to the parallel TTS models like VITS.
the final audio signal. The important downside is that Tortoise is very slow compared to the parallel TTS models like VITS.
Big thanks to 👑[@manmay-nakhashi](https://github.com/manmay-nakhashi) who helped us implement Tortoise in 🐸TTS.
@@ -12,7 +12,7 @@ from TTS.tts.configs.tortoise_config import TortoiseConfig
from TTS.tts.models.tortoise import Tortoise
config = TortoiseConfig()
model = Tortoise.inif_from_config(config)
model = Tortoise.init_from_config(config)
model.load_checkpoint(config, checkpoint_dir="paths/to/models_dir/", eval=True)
# with random speaker
@@ -29,23 +29,23 @@ from TTS.api import TTS
tts = TTS("tts_models/en/multi-dataset/tortoise-v2")
# cloning `lj` voice from `TTS/tts/utils/assets/tortoise/voices/lj`
# with custom inference settings overriding defaults.
tts.tts_to_file(text="Hello, my name is Manmay , how are you?",
# with custom inference settings overriding defaults.
tts.tts_to_file(text="Hello, my name is Manmay , how are you?",
file_path="output.wav",
voice_dir="TTS/tts/utils/assets/tortoise/voices/",
voice_dir="path/to/tortoise/voices/dir/",
speaker="lj",
num_autoregressive_samples=1,
diffusion_iterations=10)
# Using presets with the same voice
tts.tts_to_file(text="Hello, my name is Manmay , how are you?",
tts.tts_to_file(text="Hello, my name is Manmay , how are you?",
file_path="output.wav",
voice_dir="TTS/tts/utils/assets/tortoise/voices/",
voice_dir="path/to/tortoise/voices/dir/",
speaker="lj",
preset="ultra_fast")
# Random voice generation
tts.tts_to_file(text="Hello, my name is Manmay , how are you?",
tts.tts_to_file(text="Hello, my name is Manmay , how are you?",
file_path="output.wav")
```
@@ -54,16 +54,16 @@ Using 🐸TTS Command line:
```console
# cloning the `lj` voice
tts --model_name tts_models/en/multi-dataset/tortoise-v2 \
--text "This is an example." \
--out_path "/data/speech_synth/coqui-tts/TTS/tests/outputs/output.wav" \
--voice_dir TTS/tts/utils/assets/tortoise/voices/ \
--text "This is an example." \
--out_path "output.wav" \
--voice_dir path/to/tortoise/voices/dir/ \
--speaker_idx "lj" \
--progress_bar True
# Random voice generation
tts --model_name tts_models/en/multi-dataset/tortoise-v2 \
--text "This is an example." \
--out_path "/data/speech_synth/coqui-tts/TTS/tests/outputs/output.wav" \
--out_path "output.wav" \
--progress_bar True
```