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

Delete `synthesize_file.py` as it was moved to Coqui-TTS_utils repo

This commit is contained in:
Jindrich Matousek 2023-03-16 15:42:52 +01:00
parent 027d69f48b
commit c04f5046a2
1 changed files with 0 additions and 337 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

337
TTS/bin/synthesize_file.py
View File

@ -1,337 +0,0 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import argparse
from distutils.command.config import config
import sys
from argparse import RawTextHelpFormatter
# pylint: disable=redefined-outer-name, unused-argument
from pathlib import Path, PurePath
sys.path.insert(0, "/storage/plzen4-ntis/home/jmatouse/GIT_repos/Coqui-TTS.mod-0.6.1")
from TTS.utils.manage import ModelManager
from TTS.utils.synthesizer import Synthesizer
def str2bool(v):
if isinstance(v, bool):
return v
if v.lower() in ("yes", "true", "t", "y", "1"):
return True
if v.lower() in ("no", "false", "f", "n", "0"):
return False
raise argparse.ArgumentTypeError("Boolean value expected.")
def main():
# pylint: disable=bad-option-value
parser = argparse.ArgumentParser(
description="""Synthesize speech on command line.\n\n"""
"""You can either use your trained model or choose a model from the provided list.\n\n"""
"""If you don't specify any models, then it uses LJSpeech based English model.\n\n"""
"""
# Example Runs:
## Single Speaker Models
- list provided models
```
$ ./TTS/bin/synthesize.py --list_models
```
- run tts with default models.
```
$ ./TTS/bin synthesize.py --text "Text for TTS"
```
- run a tts model with its default vocoder model.
```
$ ./TTS/bin synthesize.py --text "Text for TTS" --model_name "<language>/<dataset>/<model_name>
```
- run with specific tts and vocoder models from the list
```
$ ./TTS/bin/synthesize.py --text "Text for TTS" --model_name "<language>/<dataset>/<model_name>" --vocoder_name "<language>/<dataset>/<model_name>" --output_path
```
- run your own TTS model (Using Griffin-Lim Vocoder)
```
$ ./TTS/bin/synthesize.py --text "Text for TTS" --model_path path/to/model.pth.tar --config_path path/to/config.json --out_path output/path/speech.wav
```
- run your own TTS and Vocoder models
```
$ ./TTS/bin/synthesize.py --text "Text for TTS" --model_path path/to/config.json --config_path path/to/model.pth.tar --out_path output/path/speech.wav
--vocoder_path path/to/vocoder.pth.tar --vocoder_config_path path/to/vocoder_config.json
```
## MULTI-SPEAKER MODELS
- list the available speakers and choose as <speaker_id> among them.
```
$ ./TTS/bin/synthesize.py --model_name "<language>/<dataset>/<model_name>" --list_speaker_idxs
```
- run the multi-speaker TTS model with the target speaker ID.
```
$ ./TTS/bin/synthesize.py --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.
```
$ ./TTS/bin/synthesize.py --text "Text for TTS" --out_path output/path/speech.wav --model_path path/to/config.json --config_path path/to/model.pth.tar --speakers_file_path path/to/speaker.json --speaker_idx <speaker_id>
```
""",
formatter_class=RawTextHelpFormatter,
)
parser.add_argument(
"--list_models",
type=str2bool,
nargs="?",
const=True,
default=False,
help="list available pre-trained tts and vocoder models.",
)
parser.add_argument("--text_file", type=str, default=None, help="Text file to generate speech from.")
# 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_dir",
type=str,
default="",
help="Output wav file path directory.",
)
parser.add_argument(
"--out_name",
type=str,
default="utt",
help="Output wav filename.",
)
parser.add_argument(
"--out_path",
type=str,
default="",
help="Output wav file path.",
)
parser.add_argument(
"--concat_audio",
action='store_true',
help="Concatenate audio to a single output file",
default=False
)
parser.add_argument(
"-1", "--use_infile_label",
action='store_true',
help="Use in-file label (1st word) as output file name",
default=False
)
parser.add_argument(
"--rm_last_word",
action='store_true',
help="Remove last word (typically corresponding to a pause)",
default=False
)
parser.add_argument("--use_cuda", action='store_true', help="Run model on CUDA.", default=False)
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)
# 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(
"--speaker_idx",
type=str,
help="Target speaker ID for a multi-speaker 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(
"--list_speaker_idxs",
help="List available speaker ids for the defined multi-speaker model.",
type=str2bool,
nargs="?",
const=True,
default=False,
)
# aux args
parser.add_argument(
"--save_spectogram",
action='store_true',
help="If true save raw spectogram for further (vocoder) processing in out_path.",
default=False,
)
args = parser.parse_args()
# print the description if either text or list_models is not set
if args.text_file is None and not args.list_models and not args.list_speaker_idxs:
parser.parse_args(["-h"])
# load model manager
path = Path(__file__).parent / "../.models.json"
manager = ModelManager(path)
model_path = None
config_path = None
speakers_file_path = None
vocoder_path = None
vocoder_config_path = None
encoder_path = None
encoder_config_path = None
# CASE1: list pre-trained TTS models
if args.list_models:
manager.list_models()
sys.exit()
# CASE2: load pre-trained model paths
if args.model_name is not None and not args.model_path:
model_path, config_path, model_item = manager.download_model(args.model_name)
args.vocoder_name = model_item["default_vocoder"] if args.vocoder_name is None else args.vocoder_name
if args.vocoder_name is not None and not args.vocoder_path:
vocoder_path, vocoder_config_path, _ = manager.download_model(args.vocoder_name)
# CASE3: set custom model paths
# JMa: if config is not given => use config from the corresponding model/vocoder/encoder path
if args.model_path is not None:
model_path = args.model_path
config_path = args.config_path if args.config_path else PurePath(Path(model_path).parent, "config.json")
speakers_file_path = args.speakers_file_path
if args.vocoder_path is not None:
vocoder_path = args.vocoder_path
vocoder_config_path = args.vocoder_config_path if args.vocoder_config_path else PurePath(Path(vocoder_path).parent, "config.json")
if args.encoder_path is not None:
encoder_path = args.encoder_path
encoder_config_path = args.encoder_config_path if args.encoder_config_path else PurePath(Path(encoder_path).parent, "config.json")
# load models
synthesizer = Synthesizer(
model_path,
config_path,
speakers_file_path,
vocoder_path,
vocoder_config_path,
encoder_path,
encoder_config_path,
args.use_cuda,
)
# query speaker ids of a multi-speaker model.
if args.list_speaker_idxs:
print(
" > Available speaker ids: (Set --speaker_idx flag to one of these values to use the multi-speaker model."
)
print(synthesizer.tts_model.speaker_manager.speaker_ids)
return
# check the arguments against a multi-speaker model.
if synthesizer.tts_speakers_file and (not args.speaker_idx and not args.speaker_wav):
print(
" [!] 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
# Read lines (=sentences) from the input text file
with open(args.text_file, 'rt') as fr:
lines = fr.read().splitlines()
# Resulting wav
tot_wav = []
# RUN THE SYNTHESIS line-by-line
for ix, line in enumerate(lines):
# Extract words
words = line.split()
# Use first word as utterance name?
if args.use_infile_label:
uname = words[0]
sent_beg = 1
else:
uname = "{}{:03d}".format(args.out_name, ix)
sent_beg = 0
# Remove last word?
sent_end = -1 if args.rm_last_word else len(words)
# Prepare text to synthesize
text = " ".join(words[sent_beg:sent_end])
# kick it
wav = synthesizer.tts(text, args.speaker_idx, args.speaker_wav, args.gst_style)
# Concatenate resulting wav
if args.concat_audio:
print(" > Text #{:03d}: {}".format(ix, text))
tot_wav.append(wav)
else:
# Save the wav for each line
# print(" > Saving output to {}".format(out_path))
# Prepare output path
out_path = PurePath(args.out_dir, "{}.wav".format(uname))
print(" > Text #{:03d}: {} --> {}".format(ix, text, out_path))
synthesizer.save_wav(wav, out_path)
if args.concat_audio:
# Concatenate resulting wav
print(" > Saving audio to {}".format(args.out_path))
single_wav = []
for wav in tot_wav:
single_wav.extend(list(wav))
synthesizer.save_wav(single_wav, args.out_path)
if __name__ == "__main__":
main()