Scalable Wavelet Coding of Wideband Speech and Audio

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研究针对宽带语音及音频信号的低比特率、可伸缩编码方法，采用新颖的自适应小波分解与零树编码方案，实现高质量的宽带语音与音乐传输。

http://www.ece.ucsb.edu/scl/html/prsac_4.htm

Scalable Wavelet Coding of Wideband Speech and Audio

Signal Compression Laboratory Research Project

Researcher:	Ashish Aggarwal
Faculty:	Prof. Kenneth Rose

Research Focus:

Low bit rate, scalable coding of wideband speech and audio signals is becoming increasingly important due to a growing number of applications, including audio over IP, digital audio broadcast and video-conferencing. My research interests are in developing compression methods for transmission of high quality wideband speech and music at 1-2 bps. The focus is in achieving high bit-rate and bandwidth scalability of wideband audio to aid in its transmission over packet and circuit switched networks.

The initial approach towards this end is using a novel adaptive wavelet decomposition and a zerotree coding scheme. The algorithm has the ability to adapt to varying signal characteristics, and to exploit the perceptual redundancy of the human ear while at the same time yielding a very high bit-rate scalability. Encouraging results were obtained for a 8KHz bandwidth audio signals at an output bit-rate of 30kbps. I plan to continue this work and to pursue others in the area of scalable audio coding.

For reference, please read the paper:
A. Aggarwal, V. Cuperman, K. Rose and A. Gersho, "Perceptual Zerotrees for Scalable Wavelet Coding of Wideband Audio," Proc. 1999 IEEE Workshop on Speech Coding, Pocono manor, PA, pp. 16-18, Jun. 1999.