A Fixed Rate Speech Coder with Improved Database Search

Abstract

A fixed rate speech coder having improved database search performance is proposed. In the speech coder, the 10 ms block of speech is band-passed using the filter bank, and the inflection points (IP) for each band are detected and analyzed to get the short-time statistics like the energy and IP rate. The obtained IP statistics are used to decide if the speech block is voiced or unvoiced. Then the encoder searches for the closest IP pattern either at the voiced part or at the unvoiced part of the IP database. For further reduction of the search time, the entries of the database parts corresponding to the neighboring subbands are checked for the obtained IP pattern. As results, about 94.5% decrease in search time is achieved compared to the exhaustive search. With 10 subbands and 240 entries for each band, the reconstructed signal shows about 5.2 dB SNR at 32 kbps data rate.

A Fixed Rate Speech Coder Based on the Filter Bank Method with Non-Uniform Bandwidths

“…They are points with simple slope changes (point c), and points at local maxima (point b) and local minima (point a). The inflection points are detected using following algorithm [7][8][9].…”

“…Non-uniform sampling based speech coding has been studied last 20 years [1][2][3][4][5][6][7][8][9]. Since it is non-uniform, the coding result shows variable data rate [1][2][3][4][5][6][7].…”

“…Since it is non-uniform, the coding result shows variable data rate [1][2][3][4][5][6][7]. As a remedy for this problem, the filter bank method had been proposed [8,9]. Speech signal is preprocessed with a filter bank, and the output of each bandpass filter is put into the inflection point (IP) detector.…”

“…The obtained IP patterns are compared with the entries of IP database. Thus, the information to be transmitted or stored is the address of the database, and the data rate becomes constant rather than variable [8,9]. In the decoder, the speech is reconstructed through interpolation using the received address and the IP database.…”

“…In this paper, the bandwidths of the neighboring bandpass filters becomes twice as the center frequency goes high. In addition, to facilitate the search speed of the IP database, the voiced/unvoiced detection is performed using the short-time statistics as in [9]. The difference is to use only the first bandpass filter output rather than the whole output of the filter bank to save the computation.…”