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base changes to use stdout instead of play audio
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Considering conversion to pipe wav data for audio playback with ohter program
like aplay.

This is incomplete code. Using to get feedback before proceeding with
implementation.
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@David-bfg
David-bfg committed Oct 6, 2023
1 parent 403ae73 commit f1b1f4a
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Showing 3 changed files with 185 additions and 186 deletions.
347 changes: 173 additions & 174 deletions TTS/bin/synthesize.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,7 @@

import argparse
import sys
import contextlib
from argparse import RawTextHelpFormatter

# pylint: disable=redefined-outer-name, unused-argument
Expand Down Expand Up @@ -241,7 +242,7 @@ def main():
default=None,
)
parser.add_argument(
"--play",
"--pipe_out",
help="Play the generated TTS wav.",
type=str2bool,
nargs="?",
Expand Down Expand Up @@ -361,179 +362,177 @@ def main():
if not any(check_args):
parser.parse_args(["-h"])

# Late-import to make things load faster
from TTS.api import TTS
from TTS.utils.manage import ModelManager
from TTS.utils.synthesizer import Synthesizer

# load model manager
path = Path(__file__).parent / "../.models.json"
manager = ModelManager(path, progress_bar=args.progress_bar)
api = TTS()

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

# CASE1 #list : list pre-trained TTS models
if args.list_models:
manager.add_cs_api_models(api.list_models())
manager.list_models()
sys.exit()

# CASE2 #info : model info for pre-trained TTS models
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()

# CASE3: TTS with coqui studio models
if "coqui_studio" in args.model_name:
print(" > Using 🐸Coqui Studio model: ", args.model_name)
api = TTS(model_name=args.model_name, cs_api_model=args.cs_model)
api.tts_to_file(
text=args.text,
emotion=args.emotion,
file_path=args.out_path,
language=args.language,
speed=args.speed,
play=args.play,
)
if args.play:
print(" > Played TTS wav")
print(" > Saving output to ", args.out_path)
return

# CASE4: 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)
# tts model
if model_item["model_type"] == "tts_models":
tts_path = model_path
tts_config_path = config_path
if "default_vocoder" in model_item:
args.vocoder_name = model_item["default_vocoder"] if args.vocoder_name is None else args.vocoder_name

# voice conversion model
if model_item["model_type"] == "voice_conversion_models":
vc_path = model_path
vc_config_path = config_path

# tts model with multiple files to be loaded from the directory path
if model_item.get("author", None) == "fairseq" or isinstance(model_item["model_url"], list):
model_dir = model_path
tts_path = None
tts_config_path = None
args.vocoder_name = None

# load vocoder
if args.vocoder_name is not None and not args.vocoder_path:
vocoder_path, vocoder_config_path, _ = manager.download_model(args.vocoder_name)

# CASE5: set custom model paths
if args.model_path is not None:
tts_path = args.model_path
tts_config_path = args.config_path
speakers_file_path = args.speakers_file_path
language_ids_file_path = args.language_ids_file_path

if args.vocoder_path is not None:
vocoder_path = args.vocoder_path
vocoder_config_path = args.vocoder_config_path

if args.encoder_path is not None:
encoder_path = args.encoder_path
encoder_config_path = args.encoder_config_path

device = args.device
if args.use_cuda:
device = "cuda"

# load models
synthesizer = Synthesizer(
tts_path,
tts_config_path,
speakers_file_path,
language_ids_file_path,
vocoder_path,
vocoder_config_path,
encoder_path,
encoder_config_path,
vc_path,
vc_config_path,
model_dir,
args.voice_dir,
).to(device)

# 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.name_to_id)
return

# query langauge ids of a multi-lingual model.
if args.list_language_idxs:
print(
" > Available language ids: (Set --language_idx flag to one of these values to use the multi-lingual model."
)
print(synthesizer.tts_model.language_manager.name_to_id)
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

# RUN THE SYNTHESIS
if args.text:
print(" > Text: {}".format(args.text))

# kick it
if tts_path is not None:
wav = synthesizer.tts(
args.text,
speaker_name=args.speaker_idx,
language_name=args.language_idx,
speaker_wav=args.speaker_wav,
reference_wav=args.reference_wav,
style_wav=args.capacitron_style_wav,
style_text=args.capacitron_style_text,
reference_speaker_name=args.reference_speaker_idx,
)
elif vc_path is not None:
wav = synthesizer.voice_conversion(
source_wav=args.source_wav,
target_wav=args.target_wav,
)
elif model_dir is not None:
wav = synthesizer.tts(
args.text, speaker_name=args.speaker_idx, language_name=args.language_idx, speaker_wav=args.speaker_wav
)

if args.play:
print(" > Playing TTS wav")

# save the results
print(" > Saving output to {}".format(args.out_path))
synthesizer.save_wav(wav, args.out_path, play=args.play)
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
from TTS.utils.synthesizer import Synthesizer

# load model manager
path = Path(__file__).parent / "../.models.json"
manager = ModelManager(path, progress_bar=args.progress_bar)
api = TTS()

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

# CASE1 #list : list pre-trained TTS models
if args.list_models:
manager.add_cs_api_models(api.list_models())
manager.list_models()
sys.exit()

# CASE2 #info : model info for pre-trained TTS models
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()

# CASE3: TTS with coqui studio models
if "coqui_studio" in args.model_name:
print(" > Using 🐸Coqui Studio model: ", args.model_name)
api = TTS(model_name=args.model_name, cs_api_model=args.cs_model)
api.tts_to_file(
text=args.text,
emotion=args.emotion,
file_path=args.out_path,
language=args.language,
speed=args.speed,
play=pipe_out,
)
print(" > Saving output to ", args.out_path)
return

# CASE4: 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)
# tts model
if model_item["model_type"] == "tts_models":
tts_path = model_path
tts_config_path = config_path
if "default_vocoder" in model_item:
args.vocoder_name = model_item["default_vocoder"] if args.vocoder_name is None else args.vocoder_name

# voice conversion model
if model_item["model_type"] == "voice_conversion_models":
vc_path = model_path
vc_config_path = config_path

# tts model with multiple files to be loaded from the directory path
if model_item.get("author", None) == "fairseq" or isinstance(model_item["model_url"], list):
model_dir = model_path
tts_path = None
tts_config_path = None
args.vocoder_name = None

# load vocoder
if args.vocoder_name is not None and not args.vocoder_path:
vocoder_path, vocoder_config_path, _ = manager.download_model(args.vocoder_name)

# CASE5: set custom model paths
if args.model_path is not None:
tts_path = args.model_path
tts_config_path = args.config_path
speakers_file_path = args.speakers_file_path
language_ids_file_path = args.language_ids_file_path

if args.vocoder_path is not None:
vocoder_path = args.vocoder_path
vocoder_config_path = args.vocoder_config_path

if args.encoder_path is not None:
encoder_path = args.encoder_path
encoder_config_path = args.encoder_config_path

device = args.device
if args.use_cuda:
device = "cuda"

# load models
synthesizer = Synthesizer(
tts_path,
tts_config_path,
speakers_file_path,
language_ids_file_path,
vocoder_path,
vocoder_config_path,
encoder_path,
encoder_config_path,
vc_path,
vc_config_path,
model_dir,
args.voice_dir,
).to(device)

# 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.name_to_id)
return

# query langauge ids of a multi-lingual model.
if args.list_language_idxs:
print(
" > Available language ids: (Set --language_idx flag to one of these values to use the multi-lingual model."
)
print(synthesizer.tts_model.language_manager.name_to_id)
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

# RUN THE SYNTHESIS
if args.text:
print(" > Text: {}".format(args.text))

# kick it
if tts_path is not None:
wav = synthesizer.tts(
args.text,
speaker_name=args.speaker_idx,
language_name=args.language_idx,
speaker_wav=args.speaker_wav,
reference_wav=args.reference_wav,
style_wav=args.capacitron_style_wav,
style_text=args.capacitron_style_text,
reference_speaker_name=args.reference_speaker_idx,
)
elif vc_path is not None:
wav = synthesizer.voice_conversion(
source_wav=args.source_wav,
target_wav=args.target_wav,
)
elif model_dir is not None:
wav = synthesizer.tts(
args.text, speaker_name=args.speaker_idx, language_name=args.language_idx, speaker_wav=args.speaker_wav
)

# save the results
print(" > Saving output to {}".format(args.out_path))
synthesizer.save_wav(wav, args.out_path, play=pipe_out)


if __name__ == "__main__":
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