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@ -75,3 +75,41 @@ Also, there is a `metadata.jsonl` in each subfolder. It is a table-like file tha
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### Training details can refer to the script of [examples/aishell3/tts3](../../aishell3/tts3).
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## Pretrained Model
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Pretrained FastSpeech2 model with no silence in the edge of audios:
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- [fastspeech2_canton_ckpt_1.4.0.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/fastspeech2/fastspeech2_canton_ckpt_1.4.0.zip)
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FastSpeech2 checkpoint contains files listed below.
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```text
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fastspeech2_canton_ckpt_1.4.0
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├── default.yaml # default config used to train fastspeech2
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├── energy_stats.npy # statistics used to normalize energy when training fastspeech2
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├── phone_id_map.txt # phone vocabulary file when training fastspeech2
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├── pitch_stats.npy # statistics used to normalize pitch when training fastspeech2
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├── snapshot_iter_140000.pdz # model parameters and optimizer states
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├── speaker_id_map.txt # speaker id map file when training a multi-speaker fastspeech2
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└── speech_stats.npy # statistics used to normalize spectrogram when training fastspeech2
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```
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You can use the following scripts to synthesize for `${BIN_DIR}/../sentences_canton.txt` using pretrained fastspeech2 and parallel wavegan models.
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```bash
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source path.sh
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FLAGS_allocator_strategy=naive_best_fit \
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FLAGS_fraction_of_gpu_memory_to_use=0.01 \
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python3 ${BIN_DIR}/../synthesize_e2e.py \
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--am=fastspeech2_aishell3 \
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--am_config=fastspeech2_canton_ckpt_1.4.0/default.yaml \
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--am_ckpt=fastspeech2_canton_ckpt_1.4.0/snapshot_iter_140000.pdz \
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--am_stat=fastspeech2_canton_ckpt_1.4.0/speech_stats.npy \
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--voc=pwgan_aishell3 \
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--voc_config=pwg_aishell3_ckpt_0.5/default.yaml \
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--voc_ckpt=pwg_aishell3_ckpt_0.5/snapshot_iter_1000000.pdz \
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--voc_stat=pwg_aishell3_ckpt_0.5/feats_stats.npy \
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--lang=canton \
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--text=${BIN_DIR}/../sentences_canton.txt \
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--output_dir=exp/default/test_e2e \
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--phones_dict=fastspeech2_canton_ckpt_1.4.0/phone_id_map.txt \
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--speaker_dict=fastspeech2_canton_ckpt_1.4.0/speaker_id_map.txt \
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--spk_id=0 \
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--inference_dir=exp/default/inference
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```
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