Server
Hint
Please first refer to Installation to install sherpa before proceeding.
The server is responsible for accepting audio samples from the client, decoding it, and sending the recognition results back to the client.
Usage
cd /path/to/sherpa
./sherpa/bin/lstm_transducer_stateless/streaming_server.py --help
shows the usage message.
You need the following files to start the server:
The neural network model
The
tokens.txt
.
The neural network model has three parts, the encoder, the decoder, and
the joiner, which are all exported using torch.jit.trace
.
The above files can be obtained after training your model with https://github.com/k2-fsa/icefall/tree/master/egs/wenetspeech/ASR/lstm_transducer_stateless.
If you don’t want to train a model by yourself, you can try the pretrained model: https://huggingface.co/csukuangfj/icefall-asr-wenetspeech-lstm-transducer-stateless-2022-09-19
The following shows you how to start the server with the above pretrained model.
cd /path/to/sherpa
git lfs install
git clone https://huggingface.co/csukuangfj/icefall-asr-wenetspeech-lstm-transducer-stateless-2022-09-19
./sherpa/bin/lstm_transducer_stateless/streaming_server.py \
--endpoint.rule3.min-utterance-length 1000.0 \
--port 6007 \
--max-batch-size 50 \
--max-wait-ms 5 \
--nn-pool-size 1 \
--nn-encoder-filename ./icefall-asr-wenetspeech-lstm-transducer-stateless-2022-09-19/exp/encoder_jit_trace-iter-420000-avg-10.pt \
--nn-decoder-filename ./icefall-asr-wenetspeech-lstm-transducer-stateless-2022-09-19/exp/decoder_jit_trace-iter-420000-avg-10.pt \
--nn-joiner-filename ./icefall-asr-wenetspeech-lstm-transducer-stateless-2022-09-19/exp/joiner_jit_trace-iter-420000-avg-10.pt \
--token-filename ./icefall-asr-wenetspeech-lstm-transducer-stateless-2022-09-19/data/lang_char/tokens.txt
That’s it!
Now you can start the Client, record your voice in real-time, and check the recognition results from the server.
Warning
The above pretrained model has been trained only for 6 epochs. We will update it in the following days.