Speech Recognition in Hidden Markov Modeling (HMM) Speech Recognition System

摘要

The present invention relates to a speech recognition method in a Hidden Markov Modeling (HMM) speech recognition system that reduces iterations when implementing the Viterbi algorithm, which is essential for speech recognition. In order to provide a speech recognition method which reduces the Viterbi calculation amount by performing, it is determined whether it is the last frame after initialization, and if the last frame is output, the recognition result is output, and if it is not the last frame, the Viterbi first calculation Performing a first step (401 to 404); And a second step (405, 406) of performing a linguistic processing after performing the Viterbi second calculation in word units, performing a language processing process, and repeating the last frame determination process of the first steps (401 to 404). Viterbi calculations can be significantly reduced, allowing voice recognition in real time.