HI @lissyx,
I was able to generate language model and test it using below steps. Thank-you for your help.
- Created virtualenv -
- virtualenv -p python3 $HOME/tmp/deepspeech-venv/
- source $HOME/tmp/deepspeech-venv/bin/activate
- Clone deep speech git repo branch 0.5.1 with git lfs
- git clone --branch v0.5.1 https://github.com/mozilla/DeepSpeech.git
- install the dependencies
- pip3 install -r requirement.txt
- pip3 uninstall tensorflow
- pip3 install ‘tensorflow-gpu==1.13.1’
- install CTC decoder
- pip3 install $(python3 util/taskcluster.py --decoder)
- download native_client from - https://github.com/mozilla/DeepSpeech/releases/download/v0.5.1/native_client.amd64.cuda.linux.tar.xz and extracted it into external_native_client folder in the same directory as DeepSpeech.
- Navigated to DeepSpeech/native-client ,
- Delete existing kenlm folder - rm -rf kenlm
- Clone kenlm repo - got clone https://github.com/kpu/kenlm.git
- In kenlm directory, create a build folder
- Navigate to build folder and execute
- cmake …
- make -j 4
- Form /DeepSpeech/native_client/kenlm/build/bin directory , executed
- ./lmplz --text /home/laxmikantm/proto_1/vocabulary.txt --arpa /tmp/words.arpa --order 5 --discount_fallback --temp_prefix /tmp/
- ./build_binary -T -s trie /tmp/words.arpa /tmp/lm.binary
- Now using the external_native_client files created trie file
- ./generate_trie /home/laxmikantm/DeepSpeech/data/alphabet.txt /tmp/lm.binary /tmp/trie
- After above step I had trie and lm.binary in tmp folder , I copied these files to a new folder and then used from there.
Thanks!!