A Search Complexity Improvement of Vector Quantization to Immittance Spectral Frequency Coefficients in AMR-WB Speech Codec

Abstract

An adaptive multi-rate wideband (AMR-WB) code is a speech codec developed on the basis of an algebraic code-excited linear-prediction (ACELP) coding technique, and has a double advantage of low bit rates and high speech quality. This coding technique is widely used in modern mobile communication systems for a high speech quality in handheld devices. However, a major disadvantage is that a vector quantization (VQ) of immittance spectral frequency (ISF) coefficients occupies a significant computational load in the AMR-WB encoder. Hence, this paper presents a triangular inequality elimination (TIE) algorithm combined with a dynamic mechanism and an intersection mechanism, abbreviated as the DI-TIE algorithm, to remarkably improve the complexity of ISF coefficient quantization in the AMR-WB speech codec. Both mechanisms are designed in a way that recursively enhances the performance of the TIE algorithm. At the end of this work, this proposal is experimentally validated as a superior search algorithm relative to a conventional TIE, a multiple TIE (MTIE), and an equal-average equal-variance equal-norm nearest neighbor search (EEENNS) approach. With a full search algorithm as a benchmark for search load comparison, this work provides a search load reduction above 77%, a figure far beyond 36% in the TIE, 49% in the MTIE, and 68% in the EEENNS approach.

Iterative triangular inequality elimination algorithm for codebook search of vector quantization

“…That is, the reduction in computational complexity in Ref. [8] is not as much as it appears to be. On the other hand, a binary search space-structured VQ (BSS-VQ) algorithm is adopted to reduce the complexity of ISF quantization in AMR-WB [9].…”

“…Thus, many authors [4][5][6][7][8][9] have made efforts to simplify the search complexity of an encoding process, such as approaches based on equal-average equal-variance equal-norm nearest neighbor search (EEENNS) [4,5] and those based on triangular inequality elimination (TIE) [6][7][8]. The EEENNS algorithm was derived from equal-average nearest neighbor search (ENNS) and equal-average equal-variance nearest neighbor search (EENNS) approaches.…”

“…Thus, the aim of computational load reduction can be realized. Besides, the TIE algorithm with a dynamic and an intersection mechanism [8], abbreviated as DI-TIE, was well validated to outperform the multiple TIE (MTIE) algorithm [7] and EEENNS. Nevertheless, there was hidden computational cost in DI-TIE when ruling out codewords as candidates.…”

An Upgraded Version of the Binary Search Space-Structured VQ Search Algorithm for AMR-WB Codec

“…Traditionally, a full search is employed to obtain a codeword best matched with an arbitrary input vector, and an enormous computational load is required consequently. Accordingly, efforts have been made to reduce the search complexity of an encoding process in [10][11][12][13][14][15][16][17][18], among which the binary search space-structured VQ (BSS-VQ) search algorithm in [10], a piece of our previous studies, was presented as a simple but efficient way to quantize the ISF coefficient in AMR-WB. A remarkable computational load reduction is achieved therein with a well-maintained speech quality.…”

An Efficient VQ Codebook Search Algorithm Applied to AMR-WB Speech Coding

“…Conventionally, VQ uses a full search to obtain a codeword best matched with an arbitrary input vector, but the full search requires an enormous computational load. Therefore, many studies [11][12][13][14][15][16][17][18][19] have made efforts to simplify the search complexity of an encoding process. These approaches are classified into two types in terms of the manner the complexity is reduced: triangular inequality elimination (TIE)-based approaches [11][12][13][14] and equal-average equal-variance equal-norm nearest neighbor search (EEENNS)-based algorithms [15][16][17][18][19].…”