I've been looking for a tool that can passively transcribe audio files to make them easier to search - this looks like it could almost solve that use case - maybe with a scripted tagger.
tone epub --format="markdown" --extract-sentences --one-file-per-chapter output-path/
{
"fragments": [
{
"begin": "0.000",
"children": [],
"end": "7.920",
"id": "f000001",
"language": "eng",
"lines": [
"This is the first sentence of the audio book."
]
}
}
If you are looking for something that is "ready to use", you could check out https://github.com/r4victor/syncabook or the according library https://github.com/r4victor/afaligner
If you have audio files, that are NOT audio books, the epub approach will not help you and the other comments are more helpful.
Real world data being: one on one interviews (no background noise), small groups of people chatting (lots of background noise), and specific audio recordings ( with varying British regional accents.
In all three instances whisper produced a more accurate transcription.
This is for personal use. The license of MMS is also restrictive so cannot he used for commercial uses while whisper can. Another key consideration when wondering what to choose. On the other hand, one can train MMS (so using own custom dataset) so for some projects it may be more suitable.