Speech recognition with accurate time alignment of speech units

A method comprising:

• processing, using a teacher model, one or more audio frames representative of a speech to generate a plurality of target transcription units (TUs) of the speech, wherein the plurality of target TUs comprise:
• a first plurality of tokens of the speech, and
• a second plurality of timestamps associated with the first plurality of tokens;
• and
• training, using the plurality of target TUs, a student model to generate, for a TU of the speech:
• a first set of likelihood values, an individual likelihood value of the first set of likelihood values characterizing a probability that the TU corresponds to a respective vocabulary token of a plurality of vocabulary tokens, and
• a second set of likelihood values, an individual likelihood value of the second set of likelihood values characterizing a probability that the TU is associated with a respective timestamp of a plurality of timestamps.

A system comprising:

• one or more processors to:
• process, using an automatic speech recognition (ASR) model, one or more audio frames representative of a speech to generate, for a transcription unit (TU) of the speech:
• a first set of likelihood values, an individual likelihood value of the first set of likelihood values characterizing a probability that the TU corresponds to a respective vocabulary token of a plurality of vocabulary tokens, and
• a second set of likelihood values, an individual likelihood value of the second set of likelihood values characterizing a probability that the TU corresponds to a respective timestamp token of a plurality of timestamp tokens;
• and
• generate, using the first set of likelihood values and the second set of likelihood values, a timed transcription of the speech.