Tone model enhancement for low complexity tone recognition

This paper proposes tone model enhancement for low complexity tone recognition. The tone model reduces the number of input frames by estimating fundamental frequency (F₀) from only estimated vowel signals, called vowel magnitude difference function, vowel-MDF (V_MDF). Accordingly, it reduces F₀ negative influence from neighboring syllables in continuous speech. We enhance tone recognition accuracy by more precise and low calculation vowel segmentation. This results in low complexity tone recognition making it suitable for portable equipment. In addition, the tone model is designed with parallel processing which results in real-time processing. The proposed method was tested and set by 40 Thai words, selected from voice activation for GPS systems and phone dialing options. The experimental results show 8.2% improvement in recognition accuracy, compared with the fixed vowel threshold. The tone recognition provides a 33.8% reduction in number of frames and 25.0% reduction in processing time, compared with using the entire syllable method.