Speaker-Independent Spoken Word Recognition System Based on Parallel Phoneme Labeling (PPL) Method.

This paper proposes a speaker-independent spoken-word recognition system of the following structure. The speech segments at the phoneme level are obtained by the automatic segmentation of the speech on the time axis. The segments are labeled in parallel using multiple different phoneme reference pattern sets. The symbol sequence matching between the obtained multiple phoneme lattices and the dictionary items is attempted for each phoneme lattice, which results in the recognition of the word. The effectiveness of the method is verified by an experiment. To cope with the speaker with greatly different utterance modes and voice characteristics, a separate phoneme reference pattern set is prepared. By executing the phoneme labeling in parallel using such a pattern set, one of the phoneme reference pattern sets can always be selected to handle adequately any given speech of the speaker. In other words, the phoneme sequence is recognized at the stage of the word recognition. The processing to specify the reference pattern set matched to the input speaker from the multiple phoneme reference pattern sets is no longer required at the stage of the phoneme labeling. Based on the speech data uttered by three males and three females, six phoneme reference pattern sets are constructed for each speaker. Using those pattern sets, a spoken word recognition system is constructed by the parallel phoneme labeling method. The speaker-open speech recognition experiment is executed for the phoneme- balanced 212 words uttered by six males and six females. The result is that the average recognition rate for all speakers is 88.2 percent and the lowest recognition rate for the individual speakers is 83.0 percent. Compared to the system using the speaker-independent reference pattern set obtained by mixing the six phoneme reference pattern sets for all the male and female speakers, the proposed system has the average recognition rate higher by 1.9 percent and the lowest recognition rate for the individual speakers higher by 5.2 percent. In other words, a satisfactory result is obtained as the speaker independent spoke word recognition system. [ABSTRACT FROM AUTHOR]