modified some config name and default path.
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@ -126,10 +126,10 @@ python synthesis.py \
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--checkpoint=${CHECKPOINTPATH} \
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--config='configs/ljspeech.yaml' \
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--output=${OUTPUTPATH} \
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--vocoder='griffinlim' \
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--vocoder='griffin-lim' \
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```
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We currently support two vocoders, ``griffinlim`` and ``waveflow``. You can set ``--vocoder`` to use one of them. If you want to use ``waveflow`` as your vocoder, you need to set ``--config_vocoder`` and ``--checkpoint_vocoder`` which are the path of the config and checkpoint of vocoder. You can download the pretrain model of ``waveflow`` from [here](https://github.com/PaddlePaddle/Parakeet#vocoders).
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We currently support two vocoders, ``Griffin-Lim`` algorithm and ``WaveFlow``. You can set ``--vocoder`` to use one of them. If you want to use ``waveflow`` as your vocoder, you need to set ``--config_vocoder`` and ``--checkpoint_vocoder`` which are the path of the config and checkpoint of vocoder. You can download the pre-trained model of ``waveflow`` from [here](https://github.com/PaddlePaddle/Parakeet#vocoders).
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Or you can run the script file directly.
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@ -39,8 +39,8 @@ def add_config_options_to_parser(parser):
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parser.add_argument(
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"--vocoder",
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type=str,
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default="griffinlim",
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choices=['griffinlim', 'waveflow'],
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default="griffin-lim",
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choices=['griffin-lim', 'waveflow'],
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help="vocoder method")
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parser.add_argument(
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"--config_vocoder", type=str, help="path of the vocoder config file")
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@ -53,11 +53,11 @@ def add_config_options_to_parser(parser):
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)
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parser.add_argument(
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"--checkpoint", type=str, help="fastspeech checkpoint to synthesis")
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"--checkpoint", type=str, help="fastspeech checkpoint for synthesis")
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parser.add_argument(
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"--checkpoint_vocoder",
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type=str,
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help="vocoder checkpoint to synthesis")
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help="vocoder checkpoint for synthesis")
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parser.add_argument(
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"--output",
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@ -96,7 +96,7 @@ def synthesis(text_input, args):
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_, mel_output_postnet = model(text, pos_text, alpha=args.alpha)
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if args.vocoder == 'griffinlim':
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if args.vocoder == 'griffin-lim':
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#synthesis use griffin-lim
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wav = synthesis_with_griffinlim(mel_output_postnet, cfg['audio'])
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elif args.vocoder == 'waveflow':
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@ -4,12 +4,12 @@ CUDA_VISIBLE_DEVICES=0 \
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python -u synthesis.py \
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--use_gpu=1 \
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--alpha=1.0 \
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--checkpoint='./checkpoint/fastspeech/step-162000' \
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--config='configs/ljspeech.yaml' \
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--checkpoint='./fastspeech_ljspeech_ckpt_1.0/fastspeech/step-162000' \
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--config='fastspeech_ljspeech_ckpt_1.0/ljspeech.yaml' \
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--output='./synthesis' \
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--vocoder='waveflow' \
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--config_vocoder='../waveflow/checkpoint/waveflow_res128_ljspeech_ckpt_1.0/waveflow_ljspeech.yaml' \
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--checkpoint_vocoder='../waveflow/checkpoint/waveflow_res128_ljspeech_ckpt_1.0/step-2000000' \
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--config_vocoder='./waveflow_res128_ljspeech_ckpt_1.0/waveflow_ljspeech.yaml' \
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--checkpoint_vocoder='./waveflow_res128_ljspeech_ckpt_1.0/step-2000000' \
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@ -95,10 +95,10 @@ python synthesis.py \
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--output=${OUTPUTPATH} \
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--config='configs/ljspeech.yaml' \
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--checkpoint_transformer=${CHECKPOINTPATH} \
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--vocoder='griffinlim' \
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--vocoder='griffin-lim' \
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```
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We currently support two vocoders, ``griffinlim`` and ``waveflow``. You can set ``--vocoder`` to use one of them. If you want to use ``waveflow`` as your vocoder, you need to set ``--config_vocoder`` and ``--checkpoint_vocoder`` which are the path of the config and checkpoint of vocoder. You can download the pretrain model of ``waveflow`` from [here](https://github.com/PaddlePaddle/Parakeet#vocoders).
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We currently support two vocoders, ``Griffin-Lim`` algorithm and ``WaveFlow``. You can set ``--vocoder`` to use one of them. If you want to use ``waveflow`` as your vocoder, you need to set ``--config_vocoder`` and ``--checkpoint_vocoder`` which are the path of the config and checkpoint of vocoder. You can download the pre-trained model of ``waveflow`` from [here](https://github.com/PaddlePaddle/Parakeet#vocoders).
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Or you can run the script file directly.
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@ -49,19 +49,19 @@ def add_config_options_to_parser(parser):
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parser.add_argument(
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"--checkpoint_transformer",
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type=str,
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help="transformer_tts checkpoint to synthesis")
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help="transformer_tts checkpoint for synthesis")
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parser.add_argument(
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"--vocoder",
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type=str,
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default="griffinlim",
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choices=['griffinlim', 'waveflow'],
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default="griffin-lim",
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choices=['griffin-lim', 'waveflow'],
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help="vocoder method")
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parser.add_argument(
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"--config_vocoder", type=str, help="path of the vocoder config file")
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parser.add_argument(
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"--checkpoint_vocoder",
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type=str,
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help="vocoder checkpoint to synthesis")
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help="vocoder checkpoint for synthesis")
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parser.add_argument(
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"--output",
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@ -124,7 +124,7 @@ def synthesis(text_input, args):
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i * 4 + j,
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dataformats="HWC")
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if args.vocoder == 'griffinlim':
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if args.vocoder == 'griffin-lim':
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#synthesis use griffin-lim
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wav = synthesis_with_griffinlim(postnet_pred, cfg['audio'])
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elif args.vocoder == 'waveflow':
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@ -4,11 +4,11 @@ CUDA_VISIBLE_DEVICES=0 \
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python -u synthesis.py \
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--use_gpu=0 \
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--output='./synthesis' \
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--config='configs/ljspeech.yaml' \
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--checkpoint_transformer='./checkpoint/transformer/step-120000' \
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--config='transformer_tts_ljspeech_ckpt_1.0/ljspeech.yaml' \
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--checkpoint_transformer='./transformer_tts_ljspeech_ckpt_1.0/step-120000' \
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--vocoder='waveflow' \
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--config_vocoder='../waveflow/checkpoint/waveflow_res128_ljspeech_ckpt_1.0/waveflow_ljspeech.yaml' \
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--checkpoint_vocoder='../waveflow/checkpoint/waveflow_res128_ljspeech_ckpt_1.0/step-2000000' \
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--config_vocoder='./waveflow_res128_ljspeech_ckpt_1.0/waveflow_ljspeech.yaml' \
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--checkpoint_vocoder='./waveflow_res128_ljspeech_ckpt_1.0/step-2000000' \
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if [ $? -ne 0 ]; then
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echo "Failed in training!"
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