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48 lines
1.5 KiB
48 lines
1.5 KiB
#!/bin/bash
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train_output_path=$1
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stage=0
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stop_stage=0
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# pwgan
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if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
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python3 ${BIN_DIR}/../lite_predict_streaming.py \
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--inference_dir=${train_output_path}/pdlite_streaming \
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--am=fastspeech2_csmsc \
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--am_stat=dump/train/speech_stats.npy \
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--voc=pwgan_csmsc \
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--text=${BIN_DIR}/../../assets/sentences.txt \
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--output_dir=${train_output_path}/lite_infer_out_streaming \
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--phones_dict=dump/phone_id_map.txt \
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--am_streaming=True
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fi
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# for more GAN Vocoders
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# multi band melgan
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if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
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python3 ${BIN_DIR}/../lite_predict_streaming.py \
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--inference_dir=${train_output_path}/pdlite_streaming \
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--am=fastspeech2_csmsc \
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--am_stat=dump/train/speech_stats.npy \
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--voc=mb_melgan_csmsc \
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--text=${BIN_DIR}/../../assets/sentences.txt \
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--output_dir=${train_output_path}/lite_infer_out_streaming \
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--phones_dict=dump/phone_id_map.txt \
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--am_streaming=True
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fi
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# hifigan
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if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
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python3 ${BIN_DIR}/../lite_predict_streaming.py \
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--inference_dir=${train_output_path}/pdlite_streaming \
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--am=fastspeech2_csmsc \
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--am_stat=dump/train/speech_stats.npy \
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--voc=hifigan_csmsc \
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--text=${BIN_DIR}/../../assets/sentences.txt \
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--output_dir=${train_output_path}/lite_infer_out_streaming \
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--phones_dict=dump/phone_id_map.txt \
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--am_streaming=True
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fi
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