How to prepare Audio-text data for speech recognition
In general audio training tools requires data segmented on small chunks. It is not a big problem to segment, you can use segmentation scripts, for example
segment_long_utterances.sh as described in Kaldi group discussion. Many other segmentation tools beside that like dsalign or gentle or aeneas.
Overall, training model from scratch is pretty complicated process which requires time and data (&gt;5000 hours of speech properly annotated). It can take months to build a new model.
You'd better investigate first the reasons your error rate is bad, it might not be solvable with training. If information is already lost, you can not really repair it. A better microphone, no compression for data and many other tricks can improve recognition accuracy significantly. You can also just adapt the language model to improve accuracy in case standard language model is not good for your content. It is easier than acoustic model training and you just need texts as described here.