Fast Search Methods for Spectral Quantization

✍ Scribed by John Leis; Sridha Sridharan

• Book ID: 102569449
• Publisher: Elsevier Science
• Year: 1999
• Tongue: English
• Weight: 123 KB
• Volume: 9
• Category: Article
• ISSN: 1051-2004
• DOI: 10.1006/dspr.1999.0334

✦ Synopsis

In this paper, we examine the computational requirements for the split-vector class of vector quantizers when applied to low-rate speech spectrum quantization. The split-vector quantization techniques are able to reduce the complexity and storage requirements of the 24-bit per frame spectral quantizer to manageable proportions. However, further dramatic reductions in computational complexity are possible, as will be demonstrated. As the fast-search algorithms reported in the literature are somewhat data dependent, it has been necessary to carefully evaluate several methods specifically for the speech coding problem. A total of six methods have been evaluated for their effectiveness in this task, and we show that a so-called ''geometric'' fast-search method results in a reduction in the average search time of an order of magnitude. 1999 Academic Press