mirror of https://github.com/coqui-ai/TTS.git
437 lines
14 KiB
Python
Executable File
437 lines
14 KiB
Python
Executable File
#!/usr/bin/env python3
|
|
|
|
"""Command line interface."""
|
|
|
|
import argparse
|
|
import contextlib
|
|
import logging
|
|
import sys
|
|
from argparse import RawTextHelpFormatter
|
|
|
|
# pylint: disable=redefined-outer-name, unused-argument
|
|
from TTS.utils.generic_utils import ConsoleFormatter, setup_logger
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
description = """
|
|
Synthesize speech on the command line.
|
|
|
|
You can either use your trained model or choose a model from the provided list.
|
|
|
|
- List provided models:
|
|
|
|
```sh
|
|
tts --list_models
|
|
```
|
|
|
|
- Get model information. Use the names obtained from `--list_models`.
|
|
```sh
|
|
tts --model_info_by_name "<model_type>/<language>/<dataset>/<model_name>"
|
|
```
|
|
For example:
|
|
```sh
|
|
tts --model_info_by_name tts_models/tr/common-voice/glow-tts
|
|
tts --model_info_by_name vocoder_models/en/ljspeech/hifigan_v2
|
|
```
|
|
|
|
#### Single speaker models
|
|
|
|
- Run TTS with the default model (`tts_models/en/ljspeech/tacotron2-DDC`):
|
|
|
|
```sh
|
|
tts --text "Text for TTS" --out_path output/path/speech.wav
|
|
```
|
|
|
|
- Run TTS and pipe out the generated TTS wav file data:
|
|
|
|
```sh
|
|
tts --text "Text for TTS" --pipe_out --out_path output/path/speech.wav | aplay
|
|
```
|
|
|
|
- Run a TTS model with its default vocoder model:
|
|
|
|
```sh
|
|
tts --text "Text for TTS" \\
|
|
--model_name "<model_type>/<language>/<dataset>/<model_name>" \\
|
|
--out_path output/path/speech.wav
|
|
```
|
|
|
|
For example:
|
|
|
|
```sh
|
|
tts --text "Text for TTS" \\
|
|
--model_name "tts_models/en/ljspeech/glow-tts" \\
|
|
--out_path output/path/speech.wav
|
|
```
|
|
|
|
- Run with specific TTS and vocoder models from the list. Note that not every vocoder is compatible with every TTS model.
|
|
|
|
```sh
|
|
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
|
|
```
|
|
|
|
For example:
|
|
|
|
```sh
|
|
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
|
|
```
|
|
|
|
- Run your own TTS model (using Griffin-Lim Vocoder):
|
|
|
|
```sh
|
|
tts --text "Text for TTS" \\
|
|
--model_path path/to/model.pth \\
|
|
--config_path path/to/config.json \\
|
|
--out_path output/path/speech.wav
|
|
```
|
|
|
|
- Run your own TTS and Vocoder models:
|
|
|
|
```sh
|
|
tts --text "Text for TTS" \\
|
|
--model_path path/to/model.pth \\
|
|
--config_path path/to/config.json \\
|
|
--out_path output/path/speech.wav \\
|
|
--vocoder_path path/to/vocoder.pth \\
|
|
--vocoder_config_path path/to/vocoder_config.json
|
|
```
|
|
|
|
#### Multi-speaker models
|
|
|
|
- List the available speakers and choose a `<speaker_id>` among them:
|
|
|
|
```sh
|
|
tts --model_name "<language>/<dataset>/<model_name>" --list_speaker_idxs
|
|
```
|
|
|
|
- Run the multi-speaker TTS model with the target speaker ID:
|
|
|
|
```sh
|
|
tts --text "Text for TTS." --out_path output/path/speech.wav \\
|
|
--model_name "<language>/<dataset>/<model_name>" --speaker_idx <speaker_id>
|
|
```
|
|
|
|
- Run your own multi-speaker TTS model:
|
|
|
|
```sh
|
|
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>
|
|
```
|
|
|
|
#### Voice conversion models
|
|
|
|
```sh
|
|
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>
|
|
```
|
|
"""
|
|
|
|
|
|
def parse_args() -> argparse.Namespace:
|
|
"""Parse arguments."""
|
|
parser = argparse.ArgumentParser(
|
|
description=description.replace(" ```\n", ""),
|
|
formatter_class=RawTextHelpFormatter,
|
|
)
|
|
|
|
parser.add_argument(
|
|
"--list_models",
|
|
action="store_true",
|
|
help="list available pre-trained TTS and vocoder models.",
|
|
)
|
|
|
|
parser.add_argument(
|
|
"--model_info_by_idx",
|
|
type=str,
|
|
default=None,
|
|
help="model info using query format: <model_type>/<model_query_idx>",
|
|
)
|
|
|
|
parser.add_argument(
|
|
"--model_info_by_name",
|
|
type=str,
|
|
default=None,
|
|
help="model info using query format: <model_type>/<language>/<dataset>/<model_name>",
|
|
)
|
|
|
|
parser.add_argument("--text", type=str, default=None, help="Text to generate speech.")
|
|
|
|
# Args for running pre-trained TTS models.
|
|
parser.add_argument(
|
|
"--model_name",
|
|
type=str,
|
|
default="tts_models/en/ljspeech/tacotron2-DDC",
|
|
help="Name of one of the pre-trained TTS models in format <language>/<dataset>/<model_name>",
|
|
)
|
|
parser.add_argument(
|
|
"--vocoder_name",
|
|
type=str,
|
|
default=None,
|
|
help="Name of one of the pre-trained vocoder models in format <language>/<dataset>/<model_name>",
|
|
)
|
|
|
|
# Args for running custom models
|
|
parser.add_argument("--config_path", default=None, type=str, help="Path to model config file.")
|
|
parser.add_argument(
|
|
"--model_path",
|
|
type=str,
|
|
default=None,
|
|
help="Path to model file.",
|
|
)
|
|
parser.add_argument(
|
|
"--out_path",
|
|
type=str,
|
|
default="tts_output.wav",
|
|
help="Output wav file path.",
|
|
)
|
|
parser.add_argument("--use_cuda", action="store_true", help="Run model on CUDA.")
|
|
parser.add_argument("--device", type=str, help="Device to run model on.", default="cpu")
|
|
parser.add_argument(
|
|
"--vocoder_path",
|
|
type=str,
|
|
help="Path to vocoder model file. If it is not defined, model uses GL as vocoder. Please make sure that you installed vocoder library before (WaveRNN).",
|
|
default=None,
|
|
)
|
|
parser.add_argument("--vocoder_config_path", type=str, help="Path to vocoder model config file.", default=None)
|
|
parser.add_argument(
|
|
"--encoder_path",
|
|
type=str,
|
|
help="Path to speaker encoder model file.",
|
|
default=None,
|
|
)
|
|
parser.add_argument("--encoder_config_path", type=str, help="Path to speaker encoder config file.", default=None)
|
|
parser.add_argument(
|
|
"--pipe_out",
|
|
help="stdout the generated TTS wav file for shell pipe.",
|
|
action="store_true",
|
|
)
|
|
|
|
# args for multi-speaker synthesis
|
|
parser.add_argument("--speakers_file_path", type=str, help="JSON file for multi-speaker model.", default=None)
|
|
parser.add_argument("--language_ids_file_path", type=str, help="JSON file for multi-lingual model.", default=None)
|
|
parser.add_argument(
|
|
"--speaker_idx",
|
|
type=str,
|
|
help="Target speaker ID for a multi-speaker TTS model.",
|
|
default=None,
|
|
)
|
|
parser.add_argument(
|
|
"--language_idx",
|
|
type=str,
|
|
help="Target language ID for a multi-lingual TTS model.",
|
|
default=None,
|
|
)
|
|
parser.add_argument(
|
|
"--speaker_wav",
|
|
nargs="+",
|
|
help="wav file(s) to condition a multi-speaker TTS model with a Speaker Encoder. You can give multiple file paths. The d_vectors is computed as their average.",
|
|
default=None,
|
|
)
|
|
parser.add_argument("--gst_style", help="Wav path file for GST style reference.", default=None)
|
|
parser.add_argument(
|
|
"--capacitron_style_wav", type=str, help="Wav path file for Capacitron prosody reference.", default=None
|
|
)
|
|
parser.add_argument("--capacitron_style_text", type=str, help="Transcription of the reference.", default=None)
|
|
parser.add_argument(
|
|
"--list_speaker_idxs",
|
|
help="List available speaker ids for the defined multi-speaker model.",
|
|
action="store_true",
|
|
)
|
|
parser.add_argument(
|
|
"--list_language_idxs",
|
|
help="List available language ids for the defined multi-lingual model.",
|
|
action="store_true",
|
|
)
|
|
# aux args
|
|
parser.add_argument(
|
|
"--reference_wav",
|
|
type=str,
|
|
help="Reference wav file to convert in the voice of the speaker_idx or speaker_wav",
|
|
default=None,
|
|
)
|
|
parser.add_argument(
|
|
"--reference_speaker_idx",
|
|
type=str,
|
|
help="speaker ID of the reference_wav speaker (If not provided the embedding will be computed using the Speaker Encoder).",
|
|
default=None,
|
|
)
|
|
parser.add_argument(
|
|
"--progress_bar",
|
|
action=argparse.BooleanOptionalAction,
|
|
help="Show a progress bar for the model download.",
|
|
default=True,
|
|
)
|
|
|
|
# voice conversion args
|
|
parser.add_argument(
|
|
"--source_wav",
|
|
type=str,
|
|
default=None,
|
|
help="Original audio file to convert in the voice of the target_wav",
|
|
)
|
|
parser.add_argument(
|
|
"--target_wav",
|
|
type=str,
|
|
default=None,
|
|
help="Target audio file to convert in the voice of the source_wav",
|
|
)
|
|
|
|
parser.add_argument(
|
|
"--voice_dir",
|
|
type=str,
|
|
default=None,
|
|
help="Voice dir for tortoise model",
|
|
)
|
|
|
|
args = parser.parse_args()
|
|
|
|
# print the description if either text or list_models is not set
|
|
check_args = [
|
|
args.text,
|
|
args.list_models,
|
|
args.list_speaker_idxs,
|
|
args.list_language_idxs,
|
|
args.reference_wav,
|
|
args.model_info_by_idx,
|
|
args.model_info_by_name,
|
|
args.source_wav,
|
|
args.target_wav,
|
|
]
|
|
if not any(check_args):
|
|
parser.parse_args(["-h"])
|
|
return args
|
|
|
|
|
|
def main() -> None:
|
|
"""Entry point for `tts` command line interface."""
|
|
args = parse_args()
|
|
stream = sys.stderr if args.pipe_out else sys.stdout
|
|
setup_logger("TTS", level=logging.INFO, stream=stream, formatter=ConsoleFormatter())
|
|
|
|
pipe_out = sys.stdout if args.pipe_out else None
|
|
|
|
with contextlib.redirect_stdout(None if args.pipe_out else sys.stdout):
|
|
# Late-import to make things load faster
|
|
from TTS.api import TTS
|
|
from TTS.utils.manage import ModelManager
|
|
|
|
# load model manager
|
|
manager = ModelManager(models_file=TTS.get_models_file_path(), progress_bar=args.progress_bar)
|
|
|
|
tts_path = None
|
|
tts_config_path = None
|
|
speakers_file_path = None
|
|
language_ids_file_path = None
|
|
vocoder_path = None
|
|
vocoder_config_path = None
|
|
encoder_path = None
|
|
encoder_config_path = None
|
|
vc_path = None
|
|
vc_config_path = None
|
|
model_dir = None
|
|
|
|
# 1) List pre-trained TTS models
|
|
if args.list_models:
|
|
manager.list_models()
|
|
sys.exit()
|
|
|
|
# 2) Info about pre-trained TTS models (without loading a model)
|
|
if args.model_info_by_idx:
|
|
model_query = args.model_info_by_idx
|
|
manager.model_info_by_idx(model_query)
|
|
sys.exit()
|
|
|
|
if args.model_info_by_name:
|
|
model_query_full_name = args.model_info_by_name
|
|
manager.model_info_by_full_name(model_query_full_name)
|
|
sys.exit()
|
|
|
|
# 3) Load a model for further info or TTS/VC
|
|
device = args.device
|
|
if args.use_cuda:
|
|
device = "cuda"
|
|
# A local model will take precedence if specified via modeL_path
|
|
model_name = args.model_name if args.model_path is None else None
|
|
api = TTS(
|
|
model_name=model_name,
|
|
model_path=args.model_path,
|
|
config_path=args.config_path,
|
|
vocoder_name=args.vocoder_name,
|
|
vocoder_path=args.vocoder_path,
|
|
vocoder_config_path=args.vocoder_config_path,
|
|
encoder_path=args.encoder_path,
|
|
encoder_config_path=args.encoder_config_path,
|
|
speakers_file_path=args.speakers_file_path,
|
|
language_ids_file_path=args.language_ids_file_path,
|
|
progress_bar=args.progress_bar,
|
|
).to(device)
|
|
|
|
# query speaker ids of a multi-speaker model.
|
|
if args.list_speaker_idxs:
|
|
if not api.is_multi_speaker:
|
|
logger.info("Model only has a single speaker.")
|
|
return
|
|
logger.info(
|
|
"Available speaker ids: (Set --speaker_idx flag to one of these values to use the multi-speaker model."
|
|
)
|
|
logger.info(api.speakers)
|
|
return
|
|
|
|
# query langauge ids of a multi-lingual model.
|
|
if args.list_language_idxs:
|
|
if not api.is_multi_lingual:
|
|
logger.info("Monolingual model.")
|
|
return
|
|
logger.info(
|
|
"Available language ids: (Set --language_idx flag to one of these values to use the multi-lingual model."
|
|
)
|
|
logger.info(api.languages)
|
|
return
|
|
|
|
# check the arguments against a multi-speaker model.
|
|
if api.is_multi_speaker and (not args.speaker_idx and not args.speaker_wav):
|
|
logger.error(
|
|
"Looks like you use a multi-speaker model. Define `--speaker_idx` to "
|
|
"select the target speaker. You can list the available speakers for this model by `--list_speaker_idxs`."
|
|
)
|
|
return
|
|
|
|
# RUN THE SYNTHESIS
|
|
if args.text:
|
|
logger.info("Text: %s", args.text)
|
|
|
|
if args.text is not None:
|
|
api.tts_to_file(
|
|
text=args.text,
|
|
speaker=args.speaker_idx,
|
|
language=args.language_idx,
|
|
speaker_wav=args.speaker_wav,
|
|
pipe_out=pipe_out,
|
|
file_path=args.out_path,
|
|
reference_wav=args.reference_wav,
|
|
style_wav=args.capacitron_style_wav,
|
|
style_text=args.capacitron_style_text,
|
|
reference_speaker_name=args.reference_speaker_idx,
|
|
voice_dir=args.voice_dir,
|
|
)
|
|
logger.info("Saved TTS output to %s", args.out_path)
|
|
elif args.source_wav is not None and args.target_wav is not None:
|
|
api.voice_conversion_to_file(
|
|
source_wav=args.source_wav,
|
|
target_wav=args.target_wav,
|
|
file_path=args.out_path,
|
|
pipe_out=pipe_out,
|
|
)
|
|
logger.info("Saved VC output to %s", args.out_path)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|