Received error from server (status 9) Error message: No decoder available, try again later

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C:\Users\SA>docker run --memory="8g" -it -p 8080:80 -v /media/kaldi_models:/opt/models ca9ada4fab7f /bin/bash root@b4eabf42047c:/opt# /opt/start.sh -y /opt/models/nnet2.yaml

python main.py -u ws://localhost:8080/client/ws/speech -r 8192 .\test_data_bill_gates-TED.mp3 Received error from server (status 9) Error message: No decoder available, try again later

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/nnet2.yaml You have to download TEDLIUM "online nnet2" models in order to use this sample

Run download-tedlium-nnet2.sh in '/opt/models' to download them.

use-nnet2: True decoder:

All the properties nested here correspond to the kaldinnet2onlinedecoder GStreamer plugin properties.

# Use gst-inspect-1.0 ./libgstkaldionline2.so kaldinnet2onlinedecoder to discover the available properties
use-threaded-decoder:  true
model : /opt/models/english/tedlium_nnet_ms_sp_online/final.mdl
word-syms : /opt/models/english/tedlium_nnet_ms_sp_online/words.txt
fst : /opt/models/english/tedlium_nnet_ms_sp_online/HCLG.fst
mfcc-config : /opt/models/english/tedlium_nnet_ms_sp_online/conf/mfcc.conf
ivector-extraction-config : /opt/models/english/tedlium_nnet_ms_sp_online/conf/ivector_extractor.conf
max-active: 10000
beam: 10.0
lattice-beam: 6.0
acoustic-scale: 0.083
do-endpointing : true
endpoint-silence-phones : "1:2:3:4:5:6:7:8:9:10"
traceback-period-in-secs: 0.25
chunk-length-in-secs: 0.25
num-nbest: 10
#Additional functionality that you can play with:
#lm-fst:  /opt/models/english/tedlium_nnet_ms_sp_online/G.fst
#big-lm-const-arpa: /opt/models/english/tedlium_nnet_ms_sp_online/G.carpa
#phone-syms: /opt/models/english/tedlium_nnet_ms_sp_online/phones.txt
#word-boundary-file: /opt/models/english/tedlium_nnet_ms_sp_online/word_boundary.int
#do-phone-alignment: true

out-dir: tmp

use-vad: False silence-timeout: 10

Just a sample post-processor that appends "." to the hypothesis

post-processor: perl -npe 'BEGIN {use IO::Handle; STDOUT->autoflush(1);} s/(.*)/\1./;'

A sample full post processor that add a confidence score to 1-best hyp and deletes other n-best hyps

full-post-processor: ./sample_full_post_processor.py

logging: version : 1 disable_existing_loggers: False formatters: simpleFormater: format: '%(asctime)s - %(levelname)7s: %(name)10s: %(message)s' datefmt: '%Y-%m-%d %H:%M:%S' handlers: console: class: logging.StreamHandler formatter: simpleFormater level: DEBUG root: level: DEBUG handlers: [console]