Python hparams.hparams.sentences() Examples

The following are 12 code examples of hparams.hparams.sentences(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module hparams.hparams , or try the search function .
Example #1
Source File: synthesize.py    From vae_tacotron2 with MIT License 6 votes vote down vote up 
def run_eval(args, checkpoint_path, output_dir):
	print(hparams_debug_string())
	synth = Synthesizer()
	synth.load(checkpoint_path)
	eval_dir = os.path.join(output_dir, 'eval')
	log_dir = os.path.join(output_dir, 'logs-eval')
	wav = load_wav(args.reference_audio)
	reference_mel = melspectrogram(wav).transpose()
	#Create output path if it doesn't exist
	os.makedirs(eval_dir, exist_ok=True)
	os.makedirs(log_dir, exist_ok=True)
	os.makedirs(os.path.join(log_dir, 'wavs'), exist_ok=True)
	os.makedirs(os.path.join(log_dir, 'plots'), exist_ok=True)

	with open(os.path.join(eval_dir, 'map.txt'), 'w') as file:
		for i, text in enumerate(tqdm(hparams.sentences)):
			start = time.time()
			mel_filename = synth.synthesize(text, i+1, eval_dir, log_dir, None, reference_mel)

			file.write('{}|{}\n'.format(text, mel_filename))
	print('synthesized mel spectrograms at {}'.format(eval_dir))
Example #2
Source File: synthesize.py    From gmvae_tacotron with MIT License 6 votes vote down vote up 
def run_eval(args, checkpoint_path, output_dir):
	print(hparams_debug_string())
	synth = Synthesizer()
	synth.load(checkpoint_path)
	eval_dir = os.path.join(output_dir, 'eval')
	log_dir = os.path.join(output_dir, 'logs-eval')
	wav = load_wav(args.reference_audio)
	reference_mel = melspectrogram(wav).transpose()
	#Create output path if it doesn't exist
	os.makedirs(eval_dir, exist_ok=True)
	os.makedirs(log_dir, exist_ok=True)
	os.makedirs(os.path.join(log_dir, 'wavs'), exist_ok=True)
	os.makedirs(os.path.join(log_dir, 'plots'), exist_ok=True)

	with open(os.path.join(eval_dir, 'map.txt'), 'w') as file:
		for i, text in enumerate(tqdm(hparams.sentences)):
			start = time.time()
			mel_filename = synth.synthesize(text, i+1, eval_dir, log_dir, None, reference_mel)

			file.write('{}|{}\n'.format(text, mel_filename))
	print('synthesized mel spectrograms at {}'.format(eval_dir))
Example #3
Source File: synthesize.py    From Tacotron-2 with MIT License 5 votes vote down vote up 
def get_sentences(args):
	if args.text_list != '':
		with open(args.text_list, 'rb') as f:
			sentences = list(map(lambda l: l.decode("utf-8")[:-1], f.readlines()))
	else:
		sentences = hparams.sentences
	return sentences
Example #4
Source File: synthesize.py    From Tacotron-2 with MIT License 5 votes vote down vote up 
def synthesize(args, hparams, taco_checkpoint, wave_checkpoint, sentences):
	log('Running End-to-End TTS Evaluation. Model: {}'.format(args.name or args.model))
	log('Synthesizing mel-spectrograms from text..')
	wavenet_in_dir = tacotron_synthesize(args, hparams, taco_checkpoint, sentences)
	#Delete Tacotron model from graph
	tf.reset_default_graph()
	#Sleep 1/2 second to let previous graph close and avoid error messages while Wavenet is synthesizing
	sleep(0.5)
	log('Synthesizing audio from mel-spectrograms.. (This may take a while)')
	wavenet_synthesize(args, hparams, wave_checkpoint)
	log('Tacotron-2 TTS synthesis complete!')
Example #5
Source File: synthesize.py    From tacotron2-mandarin-griffin-lim with MIT License 5 votes vote down vote up 
def get_sentences(args):
	if args.text_list != '':
		with open(args.text_list, 'rb') as f:
			sentences = list(map(lambda l: l.decode("utf-8")[:-1], f.readlines()))
	else:
		sentences = hparams.sentences
	return sentences
Example #6
Source File: synthesize.py    From tacotron2-mandarin-griffin-lim with MIT License 5 votes vote down vote up 
def main():
	accepted_modes = ['eval', 'synthesis', 'live']
	parser = argparse.ArgumentParser()
	parser.add_argument('--checkpoint', default='pretrained/', help='Path to model checkpoint')
	parser.add_argument('--hparams', default='',
		help='Hyperparameter overrides as a comma-separated list of name=value pairs')
	parser.add_argument('--name', help='Name of logging directory if the two models were trained together.')
	parser.add_argument('--tacotron_name', help='Name of logging directory of Tacotron. If trained separately')
	parser.add_argument('--wavenet_name', help='Name of logging directory of WaveNet. If trained separately')
	parser.add_argument('--model', default='Tacotron')
	parser.add_argument('--input_dir', default='training_data/', help='folder to contain inputs sentences/targets')
	parser.add_argument('--mels_dir', default='tacotron_output/eval/', help='folder to contain mels to synthesize audio from using the Wavenet')
	parser.add_argument('--output_dir', default='output/', help='folder to contain synthesized mel spectrograms')
	parser.add_argument('--mode', default='eval', help='mode of run: can be one of {}'.format(accepted_modes))
	parser.add_argument('--GTA', default='True', help='Ground truth aligned synthesis, defaults to True, only considered in synthesis mode')
	parser.add_argument('--text_list', default='', help='Text file contains list of texts to be synthesized. Valid if mode=eval')
	parser.add_argument('--speaker_id', default=None, help='Defines the speakers ids to use when running standalone Wavenet on a folder of mels. this variable must be a comma-separated list of ids')
	args = parser.parse_args()

	if args.mode not in accepted_modes:
		raise ValueError('accepted modes are: {}, found {}'.format(accepted_modes, args.mode))

	if args.GTA not in ('True', 'False'):
		raise ValueError('GTA option must be either True or False')

	taco_checkpoint, wave_checkpoint, hparams = prepare_run(args)
	sentences = get_sentences(args)

	tacotron_synthesize(args, hparams, taco_checkpoint, sentences)
Example #7
Source File: synthesize.py    From style-token_tacotron2 with MIT License 5 votes vote down vote up 
def get_sentences(args):
	if args.text_list != '':
		with open(args.text_list, 'rb') as f:
			sentences = list(map(lambda l: l.decode("utf-8")[:-1], f.readlines()))
	else:
		sentences = hparams.sentences
	return sentences
Example #8
Source File: synthesize.py    From style-token_tacotron2 with MIT License 5 votes vote down vote up 
def synthesize(args, hparams, taco_checkpoint, wave_checkpoint, sentences):
	log('Running End-to-End TTS Evaluation. Model: {}'.format(args.name or args.model))
	log('Synthesizing mel-spectrograms from text..')
	wavenet_in_dir = tacotron_synthesize(args, hparams, taco_checkpoint, sentences)
	#Delete Tacotron model from graph
	tf.reset_default_graph()
	#Sleep 1/2 second to let previous graph close and avoid error messages while Wavenet is synthesizing
	sleep(0.5)
	log('Synthesizing audio from mel-spectrograms.. (This may take a while)')
	wavenet_synthesize(args, hparams, wave_checkpoint)
	log('Tacotron-2 TTS synthesis complete!')
Example #9
Source File: interval_synthesis.py    From style-token_tacotron2 with MIT License 5 votes vote down vote up 
def get_sentences(args):
    if args.text_list != '':
        with open(args.text_list, 'rb') as f:
            sentences = list(map(lambda l: l.decode("utf-8")[:-1], f.readlines()))
    else:
        sentences = hparams.sentences
    return sentences
Example #10
Source File: interval_synthesis.py    From style-token_tacotron2 with MIT License 5 votes vote down vote up 
def synthesize(args, hparams, taco_checkpoint, wave_checkpoint, sentences):
    log('Running End-to-End TTS Evaluation. Model: {}'.format(args.name or args.model))
    log('Synthesizing mel-spectrograms from text..')
    wavenet_in_dir = tacotron_synthesize(args, hparams, taco_checkpoint, sentences)
    # Delete Tacotron model from graph
    tf.reset_default_graph()
    # Sleep 1/2 second to let previous graph close and avoid error messages while Wavenet is synthesizing
    sleep(0.5)
    log('Synthesizing audio from mel-spectrograms.. (This may take a while)')
    # wavenet_synthesize(args, hparams, wave_checkpoint)
    log('Tacotron-2 TTS synthesis complete!')
Example #11
Source File: synthesize.py    From Tacotron-2 with MIT License 4 votes vote down vote up 
def main():
	accepted_modes = ['eval', 'synthesis', 'live']
	parser = argparse.ArgumentParser()
	parser.add_argument('--checkpoint', default='pretrained/', help='Path to model checkpoint')
	parser.add_argument('--hparams', default='',
		help='Hyperparameter overrides as a comma-separated list of name=value pairs')
	parser.add_argument('--name', help='Name of logging directory if the two models were trained together.')
	parser.add_argument('--tacotron_name', help='Name of logging directory of Tacotron. If trained separately')
	parser.add_argument('--wavenet_name', help='Name of logging directory of WaveNet. If trained separately')
	parser.add_argument('--model', default='Tacotron-2')
	parser.add_argument('--input_dir', default='training_data/', help='folder to contain inputs sentences/targets')
	parser.add_argument('--mels_dir', default='tacotron_output/eval/', help='folder to contain mels to synthesize audio from using the Wavenet')
	parser.add_argument('--output_dir', default='output/', help='folder to contain synthesized mel spectrograms')
	parser.add_argument('--mode', default='eval', help='mode of run: can be one of {}'.format(accepted_modes))
	parser.add_argument('--GTA', default='True', help='Ground truth aligned synthesis, defaults to True, only considered in synthesis mode')
	parser.add_argument('--text_list', default='', help='Text file contains list of texts to be synthesized. Valid if mode=eval')
	parser.add_argument('--speaker_id', default=None, help='Defines the speakers ids to use when running standalone Wavenet on a folder of mels. this variable must be a comma-separated list of ids')
	args = parser.parse_args()

	accepted_models = ['Tacotron', 'WaveNet', 'Tacotron-2']

	if args.model not in accepted_models:
		raise ValueError('please enter a valid model to synthesize with: {}'.format(accepted_models))

	if args.mode not in accepted_modes:
		raise ValueError('accepted modes are: {}, found {}'.format(accepted_modes, args.mode))

	if args.mode == 'live' and args.model == 'Wavenet':
		raise RuntimeError('Wavenet vocoder cannot be tested live due to its slow generation. Live only works with Tacotron!')

	if args.GTA not in ('True', 'False'):
		raise ValueError('GTA option must be either True or False')

	if args.model == 'Tacotron-2':
		if args.mode == 'live':
			warn('Requested a live evaluation with Tacotron-2, Wavenet will not be used!')
		if args.mode == 'synthesis':
			raise ValueError('I don\'t recommend running WaveNet on entire dataset.. The world might end before the synthesis :) (only eval allowed)')

	taco_checkpoint, wave_checkpoint, hparams = prepare_run(args)
	sentences = get_sentences(args)

	if args.model == 'Tacotron':
		_ = tacotron_synthesize(args, hparams, taco_checkpoint, sentences)
	elif args.model == 'WaveNet':
		wavenet_synthesize(args, hparams, wave_checkpoint)
	elif args.model == 'Tacotron-2':
		synthesize(args, hparams, taco_checkpoint, wave_checkpoint, sentences)
	else:
		raise ValueError('Model provided {} unknown! {}'.format(args.model, accepted_models))
Example #12
Source File: synthesize.py    From style-token_tacotron2 with MIT License 4 votes vote down vote up 
def main():
	accepted_modes = ['eval', 'synthesis', 'live']
	parser = argparse.ArgumentParser()
	parser.add_argument('--checkpoint', default='pretrained/', help='Path to model checkpoint')
	parser.add_argument('--hparams', default='',
		help='Hyperparameter overrides as a comma-separated list of name=value pairs')
	parser.add_argument('--name', help='Name of logging directory if the two models were trained together.')
	parser.add_argument('--tacotron_name', help='Name of logging directory of Tacotron. If trained separately')
	parser.add_argument('--wavenet_name', help='Name of logging directory of WaveNet. If trained separately')
	parser.add_argument('--model', default='Tacotron-2')
	parser.add_argument('--input_dir', default='training_data/', help='folder to contain inputs sentences/targets')
	parser.add_argument('--mels_dir', default='tacotron_output/eval/', help='folder to contain mels to synthesize audio from using the Wavenet')
	parser.add_argument('--output_dir', default='output/', help='folder to contain synthesized mel spectrograms')
	parser.add_argument('--mode', default='eval', help='mode of run: can be one of {}'.format(accepted_modes))
	parser.add_argument('--GTA', default='True', help='Ground truth aligned synthesis, defaults to True, only considered in synthesis mode')
	parser.add_argument('--text_list', default='', help='Text file contains list of texts to be synthesized. Valid if mode=eval')
	parser.add_argument('--speaker_id', default=None, help='Defines the speakers ids to use when running standalone Wavenet on a folder of mels. this variable must be a comma-separated list of ids')
	args = parser.parse_args()

	accepted_models = ['Tacotron', 'WaveNet', 'Tacotron-2']

	if args.model not in accepted_models:
		raise ValueError('please enter a valid model to synthesize with: {}'.format(accepted_models))

	if args.mode not in accepted_modes:
		raise ValueError('accepted modes are: {}, found {}'.format(accepted_modes, args.mode))

	if args.mode == 'live' and args.model == 'Wavenet':
		raise RuntimeError('Wavenet vocoder cannot be tested live due to its slow generation. Live only works with Tacotron!')

	if args.GTA not in ('True', 'False'):
		raise ValueError('GTA option must be either True or False')

	if args.model == 'Tacotron-2':
		if args.mode == 'live':
			warn('Requested a live evaluation with Tacotron-2, Wavenet will not be used!')
		if args.mode == 'synthesis':
			raise ValueError('I don\'t recommend running WaveNet on entire dataset.. The world might end before the synthesis :) (only eval allowed)')

	taco_checkpoint, wave_checkpoint, hparams = prepare_run(args)
	sentences = get_sentences(args)

	if args.model == 'Tacotron':
		_ = tacotron_synthesize(args, hparams, taco_checkpoint, sentences)
	elif args.model == 'WaveNet':
		wavenet_synthesize(args, hparams, wave_checkpoint)
	elif args.model == 'Tacotron-2':
		synthesize(args, hparams, taco_checkpoint, wave_checkpoint, sentences)
	else:
		raise ValueError('Model provided {} unknown! {}'.format(args.model, accepted_models))