A hierarchical neural network model based on a C/V segmentation algorithm for isolated Mandarin speech recognition

A novel algorithm simultaneously performing consonant/vowel (C/V) segmentation and pitch detection is proposed. Based on this algorithm, a consonant enhancement method and a hierarchical neural network scheme are explored for Mandarin speech recognition. As a result, an improvement of 12% in consonant recognition rate is obtained and the number of recognition candidates is reduced from 1300 to 63. A series of experiments over all Mandarin syllables (about 1300) is demonstrated in the speaker-dependent mode. Comparisons with the decoder timer waveform algorithm are evaluated to show that the performance is satisfactory. An overall recognition rate of 90.14% is obtained