A study of noise robustness for speaker independent speech recognition method using phoneme similarity vector
Masakatsu Hoshimi, Maki K. Yamada, Katsuyuki Niyada, Shozo Makino · 1998
As an input method for rapidly spreading small portable information devices, development of speaker independent speech recognition technology which can be embedded on a single DSP is now urgently requested. We have reported a speech recognition method using phoneme similarity vector as a feature vector, which is quite robust for reduction of precision of the feature parameter. We’ve also developed a recognition board with a single DSP, which works 100-word vocabulary using only the internal memory inside the DSP. [1][2] In this report, we propose a new technique which makes our recognition method more robust, where a newly introduced noise standard template together with traditional phoneme standard templates for calculating phoneme similarity vector realizes precise word-spotting. When the newly proposed noise robustness method was tested with 100 isolated word vocabulary speech of 50 subjects, recognition accuracy of 94.7% was obtained under various noisy environments.