| 摘要 |
A line spectral frequency (LSF) vector quantizer, having particular application in digital cellular networks (DCN), is provided for code excited linear predictive (CELP) speech encoders. The LSF vector quantizer is efficient in terms of bits employed, robust and effective in terms of performance across speakers and handsets, moderate in terms of complexity, and accommodates effective and simple built-in transmission error detection schemes. The LSF vector quantizer employs a minimum number of bits, is of moderate complexity and incorporates built-in error detection capability in order to combat transmission errors. The LSF vector quantizer classifies unquantized line spectral frequencies into four categories, employing different vector quantization tables for each category. Each quantization table is optimized for particular types of vectors. For each category, three split vector codebooks are used with a simplified error measure to find three candidate split quantized vectors. The three sets of three split vectors are combined to produce as many as 27 vectors from each category. The quantizer then makes a final selection of optimal category, using a more complex error measure, to achieve the robust performance across speakers and handsets. Split vector quantization follows a two stage constrained search procedure that results in an ordered set of quantized line spectral frequencies that is "close" to the unquantized set with moderate complexity within each category. Effective and simple transmission error detection schemes at the receiver are made possible by the split nature of the vector quantization and the constrained search procedure. Only twenty-six bits are required to encode ten line spectral frequencies. <IMAGE> <IMAGE> |
