The embodiment of the invention discloses a
speech recognition method and a related device, and at least relates to a
speech recognition technology in
artificial intelligence, speech data to be recognized are used as input data of a
time delay neural network in an
acoustic model, and an output layer of the
time delay neural network comprises acoustic modeling units corresponding to a plurality of syllables respectively, so that the
speech recognition efficiency is improved. And the
syllable probability distribution corresponding to the voice frames included in the
voice data can be obtained by taking the syllables as the recognition
granularity through the
time delay neural network. When
syllable recognition is carried out through the output layer, auxiliary judgment can be carried out on the syllables to which the voice frames belong on the basis of pronunciation rules in combination with front and back
syllable information of the voice frames, so that more accurate syllable probability distribution is output. Moreover, since the syllables are generally composed of one or more phonemes, the method has higher fault-tolerant capability, not only can more accurately determine the speech recognition result based on the probability distribution of the syllables, but also has low requirements for the quality of the speech data to be recognized, and effectively expands the application scenarios of the speech recognition technology.