mirror of https://github.com/coqui-ai/TTS.git
Ensure `tts` CLI tool readme and usage help is in sync
Aarni Koskela
parent
0b95b88f13
commit
5c047cf304
136
README.md
136
README.md
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@ -294,99 +294,123 @@ api.tts_with_vc_to_file(
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```
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### Command-line `tts`
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<!-- begin-tts-readme -->
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Synthesize speech on command line.
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You can either use your trained model or choose a model from the provided list.
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If you don't specify any models, then it uses LJSpeech based English model.
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#### Single Speaker Models
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- List provided models:
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```
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$ tts --list_models
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```
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```
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$ tts --list_models
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```
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- Get model info (for both tts_models and vocoder_models):
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- Query by type/name:
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The model_info_by_name uses the name as it from the --list_models.
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```
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$ tts --model_info_by_name "<model_type>/<language>/<dataset>/<model_name>"
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```
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For example:
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```
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$ tts --model_info_by_name tts_models/tr/common-voice/glow-tts
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```
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```
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$ tts --model_info_by_name vocoder_models/en/ljspeech/hifigan_v2
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```
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- Query by type/idx:
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The model_query_idx uses the corresponding idx from --list_models.
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```
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$ tts --model_info_by_idx "<model_type>/<model_query_idx>"
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```
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For example:
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- Query by type/name:
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The model_info_by_name uses the name as it from the --list_models.
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```
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$ tts --model_info_by_name "<model_type>/<language>/<dataset>/<model_name>"
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```
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For example:
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```
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$ tts --model_info_by_name tts_models/tr/common-voice/glow-tts
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$ tts --model_info_by_name vocoder_models/en/ljspeech/hifigan_v2
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```
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- Query by type/idx:
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The model_query_idx uses the corresponding idx from --list_models.
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```
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$ tts --model_info_by_idx tts_models/3
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```
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```
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$ tts --model_info_by_idx "<model_type>/<model_query_idx>"
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```
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For example:
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```
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$ tts --model_info_by_idx tts_models/3
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```
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- Query info for model info by full name:
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```
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$ tts --model_info_by_name "<model_type>/<language>/<dataset>/<model_name>"
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```
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- Run TTS with default models:
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```
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$ tts --text "Text for TTS" --out_path output/path/speech.wav
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```
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```
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$ tts --text "Text for TTS" --out_path output/path/speech.wav
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```
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- Run a TTS model with its default vocoder model:
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```
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$ tts --text "Text for TTS" --model_name "<model_type>/<language>/<dataset>/<model_name>" --out_path output/path/speech.wav
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```
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```
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$ tts --text "Text for TTS" --model_name "<model_type>/<language>/<dataset>/<model_name>" --out_path output/path/speech.wav
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```
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For example:
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```
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$ tts --text "Text for TTS" --model_name "tts_models/en/ljspeech/glow-tts" --out_path output/path/speech.wav
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```
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```
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$ tts --text "Text for TTS" --model_name "tts_models/en/ljspeech/glow-tts" --out_path output/path/speech.wav
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```
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- Run with specific TTS and vocoder models from the list:
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```
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$ tts --text "Text for TTS" --model_name "<model_type>/<language>/<dataset>/<model_name>" --vocoder_name "<model_type>/<language>/<dataset>/<model_name>" --out_path output/path/speech.wav
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```
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```
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$ tts --text "Text for TTS" --model_name "<model_type>/<language>/<dataset>/<model_name>" --vocoder_name "<model_type>/<language>/<dataset>/<model_name>" --out_path output/path/speech.wav
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```
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For example:
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```
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$ tts --text "Text for TTS" --model_name "tts_models/en/ljspeech/glow-tts" --vocoder_name "vocoder_models/en/ljspeech/univnet" --out_path output/path/speech.wav
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```
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```
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$ tts --text "Text for TTS" --model_name "tts_models/en/ljspeech/glow-tts" --vocoder_name "vocoder_models/en/ljspeech/univnet" --out_path output/path/speech.wav
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```
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- Run your own TTS model (Using Griffin-Lim Vocoder):
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```
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$ tts --text "Text for TTS" --model_path path/to/model.pth --config_path path/to/config.json --out_path output/path/speech.wav
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```
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```
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$ tts --text "Text for TTS" --model_path path/to/model.pth --config_path path/to/config.json --out_path output/path/speech.wav
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```
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- Run your own TTS and Vocoder models:
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```
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$ tts --text "Text for TTS" --model_path path/to/model.pth --config_path path/to/config.json --out_path output/path/speech.wav
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--vocoder_path path/to/vocoder.pth --vocoder_config_path path/to/vocoder_config.json
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```
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```
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$ tts --text "Text for TTS" --model_path path/to/model.pth --config_path path/to/config.json --out_path output/path/speech.wav
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--vocoder_path path/to/vocoder.pth --vocoder_config_path path/to/vocoder_config.json
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```
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#### Multi-speaker Models
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- List the available speakers and choose a <speaker_id> among them:
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```
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$ tts --model_name "<language>/<dataset>/<model_name>" --list_speaker_idxs
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```
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```
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$ tts --model_name "<language>/<dataset>/<model_name>" --list_speaker_idxs
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```
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- Run the multi-speaker TTS model with the target speaker ID:
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```
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$ tts --text "Text for TTS." --out_path output/path/speech.wav --model_name "<language>/<dataset>/<model_name>" --speaker_idx <speaker_id>
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```
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```
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$ tts --text "Text for TTS." --out_path output/path/speech.wav --model_name "<language>/<dataset>/<model_name>" --speaker_idx <speaker_id>
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```
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- Run your own multi-speaker TTS model:
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```
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$ tts --text "Text for TTS" --out_path output/path/speech.wav --model_path path/to/model.pth --config_path path/to/config.json --speakers_file_path path/to/speaker.json --speaker_idx <speaker_id>
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```
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```
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$ tts --text "Text for TTS" --out_path output/path/speech.wav --model_path path/to/model.pth --config_path path/to/config.json --speakers_file_path path/to/speaker.json --speaker_idx <speaker_id>
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```
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### Voice Conversion Models
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```
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$ tts --out_path output/path/speech.wav --model_name "<language>/<dataset>/<model_name>" --source_wav <path/to/speaker/wav> --target_wav <path/to/reference/wav>
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```
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<!-- end-tts-readme -->
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## Directory Structure
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```
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@ -12,6 +12,121 @@ from TTS.api import TTS
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from TTS.utils.manage import ModelManager
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from TTS.utils.synthesizer import Synthesizer
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description = """
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Synthesize speech on command line.
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You can either use your trained model or choose a model from the provided list.
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If you don't specify any models, then it uses LJSpeech based English model.
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#### Single Speaker Models
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- List provided models:
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```
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$ tts --list_models
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```
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- Get model info (for both tts_models and vocoder_models):
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- Query by type/name:
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The model_info_by_name uses the name as it from the --list_models.
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```
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$ tts --model_info_by_name "<model_type>/<language>/<dataset>/<model_name>"
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```
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For example:
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```
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$ tts --model_info_by_name tts_models/tr/common-voice/glow-tts
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$ tts --model_info_by_name vocoder_models/en/ljspeech/hifigan_v2
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```
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- Query by type/idx:
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The model_query_idx uses the corresponding idx from --list_models.
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```
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$ tts --model_info_by_idx "<model_type>/<model_query_idx>"
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```
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For example:
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```
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$ tts --model_info_by_idx tts_models/3
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```
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- Query info for model info by full name:
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```
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$ tts --model_info_by_name "<model_type>/<language>/<dataset>/<model_name>"
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```
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- Run TTS with default models:
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```
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$ tts --text "Text for TTS" --out_path output/path/speech.wav
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```
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- Run a TTS model with its default vocoder model:
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```
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$ tts --text "Text for TTS" --model_name "<model_type>/<language>/<dataset>/<model_name>" --out_path output/path/speech.wav
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```
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For example:
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```
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$ tts --text "Text for TTS" --model_name "tts_models/en/ljspeech/glow-tts" --out_path output/path/speech.wav
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```
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- Run with specific TTS and vocoder models from the list:
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```
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$ tts --text "Text for TTS" --model_name "<model_type>/<language>/<dataset>/<model_name>" --vocoder_name "<model_type>/<language>/<dataset>/<model_name>" --out_path output/path/speech.wav
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```
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For example:
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```
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$ tts --text "Text for TTS" --model_name "tts_models/en/ljspeech/glow-tts" --vocoder_name "vocoder_models/en/ljspeech/univnet" --out_path output/path/speech.wav
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```
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- Run your own TTS model (Using Griffin-Lim Vocoder):
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```
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$ tts --text "Text for TTS" --model_path path/to/model.pth --config_path path/to/config.json --out_path output/path/speech.wav
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```
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- Run your own TTS and Vocoder models:
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```
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$ tts --text "Text for TTS" --model_path path/to/model.pth --config_path path/to/config.json --out_path output/path/speech.wav
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--vocoder_path path/to/vocoder.pth --vocoder_config_path path/to/vocoder_config.json
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```
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#### Multi-speaker Models
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- List the available speakers and choose a <speaker_id> among them:
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```
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$ tts --model_name "<language>/<dataset>/<model_name>" --list_speaker_idxs
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```
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- Run the multi-speaker TTS model with the target speaker ID:
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```
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$ tts --text "Text for TTS." --out_path output/path/speech.wav --model_name "<language>/<dataset>/<model_name>" --speaker_idx <speaker_id>
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```
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- Run your own multi-speaker TTS model:
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```
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$ tts --text "Text for TTS" --out_path output/path/speech.wav --model_path path/to/model.pth --config_path path/to/config.json --speakers_file_path path/to/speaker.json --speaker_idx <speaker_id>
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```
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### Voice Conversion Models
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```
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$ tts --out_path output/path/speech.wav --model_name "<language>/<dataset>/<model_name>" --source_wav <path/to/speaker/wav> --target_wav <path/to/reference/wav>
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```
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"""
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def str2bool(v):
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if isinstance(v, bool):
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@ -24,92 +139,6 @@ def str2bool(v):
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def main():
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description = """Synthesize speech on command line.
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You can either use your trained model or choose a model from the provided list.
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If you don't specify any models, then it uses LJSpeech based English model.
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## Example Runs
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### Single Speaker Models
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- List provided models:
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```
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$ tts --list_models
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```
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- Query info for model info by idx:
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```
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$ tts --model_info_by_idx "<model_type>/<model_query_idx>"
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```
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- Query info for model info by full name:
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```
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$ tts --model_info_by_name "<model_type>/<language>/<dataset>/<model_name>"
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```
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- Run TTS with default models:
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```
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$ tts --text "Text for TTS"
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```
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- Run a TTS model with its default vocoder model:
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```
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$ tts --text "Text for TTS" --model_name "<model_type>/<language>/<dataset>/<model_name>
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```
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- Run with specific TTS and vocoder models from the list:
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```
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$ tts --text "Text for TTS" --model_name "<model_type>/<language>/<dataset>/<model_name>" --vocoder_name "<model_type>/<language>/<dataset>/<model_name>" --output_path
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```
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- Run your own TTS model (Using Griffin-Lim Vocoder):
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```
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$ tts --text "Text for TTS" --model_path path/to/model.pth --config_path path/to/config.json --out_path output/path/speech.wav
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```
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- Run your own TTS and Vocoder models:
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```
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$ tts --text "Text for TTS" --model_path path/to/config.json --config_path path/to/model.pth --out_path output/path/speech.wav
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--vocoder_path path/to/vocoder.pth --vocoder_config_path path/to/vocoder_config.json
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```
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### Multi-speaker Models
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- List the available speakers and choose as <speaker_id> among them:
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```
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$ tts --model_name "<language>/<dataset>/<model_name>" --list_speaker_idxs
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```
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- Run the multi-speaker TTS model with the target speaker ID:
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```
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$ tts --text "Text for TTS." --out_path output/path/speech.wav --model_name "<language>/<dataset>/<model_name>" --speaker_idx <speaker_id>
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```
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- Run your own multi-speaker TTS model:
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```
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$ tts --text "Text for TTS" --out_path output/path/speech.wav --model_path path/to/config.json --config_path path/to/model.pth --speakers_file_path path/to/speaker.json --speaker_idx <speaker_id>
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```
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### Voice Conversion Models
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```
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$ tts --out_path output/path/speech.wav --model_name "<language>/<dataset>/<model_name>" --source_wav <path/to/speaker/wav> --target_wav <path/to/reference/wav>
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```
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"""
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# We remove Markdown code formatting programmatically here to allow us to copy-and-paste from main README to keep
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# documentation in sync more easily.
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parser = argparse.ArgumentParser(
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description=description.replace(" ```\n", ""),
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formatter_class=RawTextHelpFormatter,
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@ -0,0 +1,32 @@
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import argparse
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from pathlib import Path
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def replace_between_markers(content, marker: str, replacement: str) -> str:
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start_marker = f"<!-- begin-{marker} -->\n\n"
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end_marker = f"\n\n<!-- end-{marker} -->\n"
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start_index = content.index(start_marker) + len(start_marker)
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end_index = content.index(end_marker)
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content = content[:start_index] + replacement + content[end_index:]
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return content
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def sync_readme():
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ap = argparse.ArgumentParser()
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ap.add_argument("--check", action="store_true", default=False)
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args = ap.parse_args()
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readme_path = Path(__file__).parent.parent / "README.md"
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orig_content = readme_path.read_text()
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from TTS.bin.synthesize import description
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new_content = replace_between_markers(orig_content, "tts-readme", description.strip())
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if args.check:
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if orig_content != new_content:
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print("README.md is out of sync; please edit TTS/bin/TTS_README.md and run scripts/sync_readme.py")
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exit(42)
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readme_path.write_text(new_content)
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print("Updated README.md")
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if __name__ == "__main__":
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sync_readme()
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@ -0,0 +1,9 @@
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import subprocess
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import sys
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from pathlib import Path
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def test_readme_up_to_date():
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root = Path(__file__).parent.parent.parent
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sync_readme = root / "scripts" / "sync_readme.py"
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subprocess.check_call([sys.executable, str(sync_readme), "--check"], cwd=root)
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