A low power tone recognition for automatic tonal speech recognizer

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Publication Details

Author list: Chaiwongsai J., Chiracharit W., Chamnongthai K., Miyanaga Y., Higuchi K.

Publisher: Institute of Electronics, Information and Communication Engineers

Publication year: 2013

Volume number: E96-A

Issue number: 6

Start page: 1403

End page: 1411

Number of pages: 9

ISSN: 0916-8508

eISSN: 1745-1337

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84878541846&doi=10.1587%2ftransfun.E96.A.1403&partnerID=40&md5=14402f688633c7974c1b38c3ad6477bb

Languages: English-Great Britain (EN-GB)

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Abstract

This paper proposes a low power tone recognition suitable for automatic tonal speech recognizer (ATSR). The tone recognition estimates fundamental frequency (F0) only from vowels by using a new magnitude difference function (MDF), called vowel-MDF. Accordingly, the number of operations is considerably reduced. In order to apply the tone recognition in portable electronic equipment, the tone recognition is designed using parallel and pipeline architecture. Due to the pipeline and parallel computations, the architecture achieves high throughput and consumes low power. In addition, the architecture is able to reduce the number of input frames depending on vowels, making it more adaptable depending on the maximum number of frames. The proposed architecture is evaluated with words selected from voice activation for GPS systems, phone dialing options, and words having the same phoneme but different tones. In comparison with the autocorrelation method, the experimental results show 35.7% reduction in power consumption and 27.1% improvement of tone recognition accuracy (110 words comprising 187 syllables). In comparison with ATSR without the tone recognition, the speech recognition accuracy indicates 25.0% improvement of ATSR with tone recogntion (2,250 training data and 45 testing words). Copyright ฉ 2013 The Institute of Electronics, Information and Communication Engineers.

Keywords

ATSR, Pipeline and parallel architecture, Tone recognition, Vowel-MDF