Token confidence scores for automatic speech recognition

A computer-implemented method for speech recognition, comprising:

• generating, based on an acoustic model, a plurality of phoneme sequences of an utterance;
• assigning sentence-level acoustic scores to individual phoneme sequences to indicate the likelihood of correctness to represent the utterance;
• receiving, at an acoustic model of an automatic speech recognition system, a plurality of tokens and phrases representing the utterance;
• assigning, by a confidence score model, respective token confidence scores and phrase confidence scores to the plurality of tokens and phrases, wherein a token confidence score and phrase confidence score represent a level of confidence of the correct representation of a word or phrase;
• determining, by a translation model, that a first confidence score associated with a phrase is lower than a predetermined threshold;
• determining a substitute phrase associated with a second confidence score that is higher than the first confidence score;
• and
• replacing the phrase with the substitute phrase to generate an updated phoneme sequence.

A computer-implemented method for speech recognition, comprising:

• receiving, at an automatic speech recognition system, an utterance;
• generating, based on an acoustic model, a phoneme sequence of the utterance;
• generating, based on the acoustic model, a plurality of phoneme sequences of the utterance that comprise the phoneme sequence;
• assigning sentence-level acoustic scores to individual phoneme sequences to indicate the likelihood of correctness to represent the utterance;
• segmenting the phoneme sequence into a token sequence that represents the phoneme sequence based on a pronunciation dictionary;
• assigning respective token confidence scores to individual tokens in the token sequence, wherein a token confidence score represents a level of confidence of the correct representation of a tokenized word;
• determining that a first confidence score associated with a token is lower than a predetermined threshold;
• determining a substitute token associated with a second confidence score that is higher than the first confidence score;
• updating the token sequence by replacing the token with the substitute token;
• and
• determining a phoneme hypothesis from the plurality of phoneme sequences to represent the utterance.