Closed LqNoob closed 5 years ago
I guess some of the factors that have an impact on the decoding latency are audio throughput latency (how fast the audio arrives to the server) and speech quality: clear speech with little background noise is just faster to decode (because of pruning).
Thank you for your reply! By testing kaldi's online decoding(online2-wav-nnet2-latgen-faster.cc), it is found that a large part of the time is wasted on reading and processing the audio that have chunk length size. Now, I don't know how to deal with this problem.
I just started studying kaldi, and see the project on GitHub. I want to know if the project gst-kaldi-nnet2-online only support the ivector feature, Is the input feature only mfcc/fbank, otherwise it won't work, or If I use other features, just change the configuration file
It does support i-vectors. Only mfcc/fbank features are supported.
thank you very much
Sometimes we may wait a few seconds for ASR system to process a piece of audio. How did you solve this situation? How to improve the speed of recognition?
The question is "How did you get the results immediately as user stopped speaking?"