Speech recognition is becoming popular in current development on mobile devices. Presumably, mobile devices have limited computational power, memory size and battery life. In general, speech recognition is a heavy process that required large sample data within each window. Fast Fourier Transform (FFT) is the most popular transform in speech recognition. In addition, FFT operates in complex field with imaginary numbers. This paper proposes an approach based on discrete orthonormal Tchebichef polynomials as a possible alternative to FFT. Discrete Tchebichef Transform (DTT) shall be utilized here instead of FFT. The preliminary experimental result shows that speech recognition using DTT produces a simpler and efficient transformation for speech recognition. The frequency formants using FFT and DTT have been compared. The result showed that, they have produced relatively identical output in term of basic vowel and consonant recognition. DTT has the potential to provide simpler computing with DTT coefficient real numbers only than FFT on speech recognition.

Date Published: 13 January 2012
PDF: 5 pages
Proc. SPIE 8350, Fourth International Conference on Machine Vision (ICMV 2011): Computer Vision and Image Analysis; Pattern Recognition and Basic Technologies, 83501J (13 January 2012); doi: 10.1117/12.920206

Published in SPIE Proceedings Vol. 8350:
Fourth International Conference on Machine Vision (ICMV 2011): Computer Vision and Image Analysis; Pattern Recognition and Basic Technologies
Safaa S. Mahmoud; Zhu Zeng; Yuting Li, Editor(s)