run.sh 1.3 KB

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  1. #!/usr/bin/env bash
  2. if [ ! -d ./sherpa-ncnn-streaming-zipformer-bilingual-zh-en-2023-02-13 ]; then
  3. echo "Please download the pre-trained model for testing."
  4. echo "You can refer to"
  5. echo ""
  6. echo "https://k2-fsa.github.io/sherpa/ncnn/pretrained_models/zipformer-transucer-models.html#csukuangfj-sherpa-ncnn-streaming-zipformer-bilingual-zh-en-2023-02-13-bilingual-chinese-english"
  7. echo ""
  8. echo "for help"
  9. exit 1
  10. fi
  11. go build
  12. ./decode-file \
  13. --encoder-param ./sherpa-ncnn-streaming-zipformer-bilingual-zh-en-2023-02-13/encoder_jit_trace-pnnx.ncnn.param \
  14. --encoder-bin ./sherpa-ncnn-streaming-zipformer-bilingual-zh-en-2023-02-13/encoder_jit_trace-pnnx.ncnn.bin \
  15. --decoder-param ./sherpa-ncnn-streaming-zipformer-bilingual-zh-en-2023-02-13/decoder_jit_trace-pnnx.ncnn.param \
  16. --decoder-bin ./sherpa-ncnn-streaming-zipformer-bilingual-zh-en-2023-02-13/decoder_jit_trace-pnnx.ncnn.bin \
  17. --joiner-param ./sherpa-ncnn-streaming-zipformer-bilingual-zh-en-2023-02-13/joiner_jit_trace-pnnx.ncnn.param \
  18. --joiner-bin ./sherpa-ncnn-streaming-zipformer-bilingual-zh-en-2023-02-13/joiner_jit_trace-pnnx.ncnn.bin \
  19. --tokens ./sherpa-ncnn-streaming-zipformer-bilingual-zh-en-2023-02-13/tokens.txt \
  20. ./sherpa-ncnn-streaming-zipformer-bilingual-zh-en-2023-02-13/test_wavs/1.wav