Training an automatic speech recognition system

Plan an ASR training workflow from paired recordings and transcripts to an evaluated checkpoint. Distinguish audio features from model layers, declared dataset assumptions from published corpus totals, and training throughput from transcript-generation speed.

Automatic speech recognition (ASR) converts speech into text. Applications include transcription, voice search, assistants, and captions. The output should represent what was spoken, rather than silently paraphrasing it into a more plausible sentence.