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TTS
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Update README with new device API (#2876) 

* docs: update readme w/ .to(device) api

* docs: add .to(device) in python quickstart

* docs: move section header out of comment

* chore: use device instead of hard-coded string

* docs: update inference.md
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Jake Tae 2023-08-28 05:19:00 -04:00 committed by GitHub
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21
README.md
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@ -187,18 +187,21 @@ More details about the docker images (like GPU support) can be found [here](http
### 🐍 Python API
#### Running a multi-speaker and multi-lingual model
```python
import torch
from TTS.api import TTS
# Running a multi-speaker and multi-lingual model
# Get device
device = "cuda" if torch.cuda.is_available() else "cpu"
# List available 🐸TTS models and choose the first one
model_name = TTS.list_models()[0]
model_name = TTS().list_models()[0]
# Init TTS
tts = TTS(model_name)
tts = TTS(model_name).to(device)
# Run TTS
# ❗ Since this model is multi-speaker and multi-lingual, we must set the target speaker and the language
# Text to speech with a numpy output
wav = tts.tts("This is a test! This is also a test!!", speaker=tts.speakers[0], language=tts.languages[0])
@ -210,13 +213,13 @@ tts.tts_to_file(text="Hello world!", speaker=tts.speakers[0], language=tts.langu
```python
# Init TTS with the target model name
tts = TTS(model_name="tts_models/de/thorsten/tacotron2-DDC", progress_bar=False, gpu=False)
tts = TTS(model_name="tts_models/de/thorsten/tacotron2-DDC", progress_bar=False).to(device)
# Run TTS
tts.tts_to_file(text="Ich bin eine Testnachricht.", file_path=OUTPUT_PATH)
# Example voice cloning with YourTTS in English, French and Portuguese
tts = TTS(model_name="tts_models/multilingual/multi-dataset/your_tts", progress_bar=False, gpu=True)
tts = TTS(model_name="tts_models/multilingual/multi-dataset/your_tts", progress_bar=False).to(device)
tts.tts_to_file("This is voice cloning.", speaker_wav="my/cloning/audio.wav", language="en", file_path="output.wav")
tts.tts_to_file("C'est le clonage de la voix.", speaker_wav="my/cloning/audio.wav", language="fr-fr", file_path="output.wav")
tts.tts_to_file("Isso é clonagem de voz.", speaker_wav="my/cloning/audio.wav", language="pt-br", file_path="output.wav")
@ -227,7 +230,7 @@ tts.tts_to_file("Isso é clonagem de voz.", speaker_wav="my/cloning/audio.wav",
Converting the voice in `source_wav` to the voice of `target_wav`
```python
tts = TTS(model_name="voice_conversion_models/multilingual/vctk/freevc24", progress_bar=False, gpu=True)
tts = TTS(model_name="voice_conversion_models/multilingual/vctk/freevc24", progress_bar=False).to("cuda")
tts.voice_conversion_to_file(source_wav="my/source.wav", target_wav="my/target.wav", file_path="output.wav")
```
@ -256,7 +259,7 @@ These models will follow the naming convention `coqui_studio/en/<studio_speaker_
# XTTS model
models = TTS(cs_api_model="XTTS").list_models()
# Init TTS with the target studio speaker
tts = TTS(model_name="coqui_studio/en/Torcull Diarmuid/coqui_studio", progress_bar=False, gpu=False)
tts = TTS(model_name="coqui_studio/en/Torcull Diarmuid/coqui_studio", progress_bar=False)
# Run TTS
tts.tts_to_file(text="This is a test.", file_path=OUTPUT_PATH)

12
docs/source/inference.md
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@ -117,7 +117,7 @@ You can run a multi-speaker and multi-lingual model in Python as
from TTS.api import TTS
# List available 🐸TTS models and choose the first one
model_name = TTS.list_models()[0]
model_name = TTS().list_models()[0]
# Init TTS
tts = TTS(model_name)
# Run TTS
@ -132,7 +132,7 @@ tts.tts_to_file(text="Hello world!", speaker=tts.speakers[0], language=tts.langu
```python
# Init TTS with the target model name
tts = TTS(model_name="tts_models/de/thorsten/tacotron2-DDC", progress_bar=False, gpu=False)
tts = TTS(model_name="tts_models/de/thorsten/tacotron2-DDC", progress_bar=False)
# Run TTS
tts.tts_to_file(text="Ich bin eine Testnachricht.", file_path=OUTPUT_PATH)
```
@ -140,7 +140,7 @@ tts.tts_to_file(text="Ich bin eine Testnachricht.", file_path=OUTPUT_PATH)
#### Example voice cloning with YourTTS in English, French and Portuguese:
```python
tts = TTS(model_name="tts_models/multilingual/multi-dataset/your_tts", progress_bar=False, gpu=True)
tts = TTS(model_name="tts_models/multilingual/multi-dataset/your_tts", progress_bar=False).to("cuda")
tts.tts_to_file("This is voice cloning.", speaker_wav="my/cloning/audio.wav", language="en", file_path="output.wav")
tts.tts_to_file("C'est le clonage de la voix.", speaker_wav="my/cloning/audio.wav", language="fr", file_path="output.wav")
tts.tts_to_file("Isso é clonagem de voz.", speaker_wav="my/cloning/audio.wav", language="pt", file_path="output.wav")
@ -149,7 +149,7 @@ tts.tts_to_file("Isso é clonagem de voz.", speaker_wav="my/cloning/audio.wav",
#### Example voice conversion converting speaker of the `source_wav` to the speaker of the `target_wav`
```python
tts = TTS(model_name="voice_conversion_models/multilingual/vctk/freevc24", progress_bar=False, gpu=True)
tts = TTS(model_name="voice_conversion_models/multilingual/vctk/freevc24", progress_bar=False).to("cuda")
tts.voice_conversion_to_file(source_wav="my/source.wav", target_wav="my/target.wav", file_path="output.wav")
```
@ -177,7 +177,7 @@ You should set the `COQUI_STUDIO_TOKEN` environment variable to use the API toke
# The name format is coqui_studio/en/<studio_speaker_name>/coqui_studio
models = TTS().list_models()
# Init TTS with the target studio speaker
tts = TTS(model_name="coqui_studio/en/Torcull Diarmuid/coqui_studio", progress_bar=False, gpu=False)
tts = TTS(model_name="coqui_studio/en/Torcull Diarmuid/coqui_studio", progress_bar=False)
# Run TTS
tts.tts_to_file(text="This is a test.", file_path=OUTPUT_PATH)
# Run TTS with emotion and speed control
@ -222,7 +222,7 @@ You can find the list of language ISO codes [here](https://dl.fbaipublicfiles.co
```python
from TTS.api import TTS
api = TTS(model_name="tts_models/eng/fairseq/vits", gpu=True)
api = TTS(model_name="tts_models/eng/fairseq/vits").to("cuda")
api.tts_to_file("This is a test.", file_path="output.wav")
# TTS with on the fly voice conversion