How can I integrate a language model in a tensorflow speech recognition architecture?
There are a bunch of examples out there for building character level speech recognition in Tensorflow (e.g. https://github.com/nervanasystems/neon, https://github.com/buriburisuri/speech-to-text-wavenet), which is interesting but practically useless, unless a language model is integrated. I couldn't find an example that uses a language model.
How can I integrate a language model?
LM scoring is just an additional rescoring step, simply a spelling correction with a language model. It can be applied on any system output. Mozilla has it spell.py for example.