Comments (2)
Sure
- Try to improve the quality of the audio. Think about better microphones, less lossy encoding-decoding, closer microphone
- Train better acoustic models
This is not really a question about a server
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Try training your acoustic models using reverbareted and noised training data. But yes, it's not a question about the server.
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Related Issues (20)
- python kaldigstserver/client.py -r 32000 test/data/english_test.raw gives only THE. as output
- single word audio file gives multiple results, how to choose the correct result? HOT 1
- gstkaldinnet2onlinedecoder vs online2-tcp-nnet3-decoder-faster HOT 7
- The pretrained Chinese model can not process audio file with 48khz sample rate HOT 1
- Error switching between Audio types
- Error when running python kaldigstserver/worker.py on sample chinese HOT 1
- How to get phone alignment and word alignment information
- decoder with CSJ -> worker: segmentation fault (core dumped) HOT 2
- Enable Multiple channels listening HOT 1
- setting up the server for http api call HOT 2
- INTEL MKL ERROR: /opt/intel/mkl/lib/intel64/libmkl_avx2.so: undefined symbol: mkl_sparse_optimize_bsr_trsm_i8. Intel MKL FATAL ERROR: Cannot load libmkl_avx2.so or libmkl_def.so. HOT 2
- server can not get EOS HOT 1
- when I run it in doocker and use the chinese model ,it have this question :2021-04-16 05:52:17 - INFO: __main__: 7404beee-0d39-4d67-963c-01c58da10193: Waiting for EOS from decoder 2021-04-16 05:52:18 - INFO: __main__: 7404beee-0d39-4d67-963c-01c58da10193: Waiting for EOS from decoder HOT 2
- How to run multiple models in a single machine
- How can I save the incoming audio stream to wav file ?
- Invalid parameters supplied to OnlineLdaInput
- cannot download tedlium_nnet_ms_sp_online.tgz HOT 3
- worker process killed when worker replications reach to 3
- Poor performance with nnet3 TDNN-F model
- Any updates of year 2023???
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