An Improvement of the Triangular Inequality Elimination Algorithm for Vector Quantization

Abstract: This study proposes an improvement of the triangular inequality elimination (TIE) algorithm for vector quantization (VQ). More than 26% additional computation saving is achieved. The proposed approach uses dynamic and intersection (DI) rules to recursively compensate and enhance the TIE algorithm. The dynamic rule changes the reference codeword dynamically and reaches the smallest candidate group. The intersection rule removes redundant codewords from these candidate groups. The DI-TIE approach avoids the over-reliance on continuity of input signal. The VQ-based line spectral pair (LSP) quantization in ITU-T G.729 standard and some standard test images are used to test the contribution of the DI-TIE. Experimental results confirm that the DI rules in the TIE algorithm have an excellent performance. Moreover, in comparison with the quasi-binary search (QBS) approach, both the QBS and the DI-TIE methods are independent on the continuity of input signal. Nevertheless, the DI-TIE approach proposed in the paper is superior to the QBS method in the computation saving issue

Efficient Detection Approach for DTMF Signal Detection

A novel tone detection approach, designated as the multi-frequency detecting (MFD) algorithm, is presented in this work as an alternative to conventional single point detection approaches but it is an efficient way to achieve the aim of further computational load reduction for a dual-tone multi-frequency (DTMF) signal detection. The idea is that an optimal phase search is performed over the frequency band of interest in each tone detection, and then the optimal frequency response of a detector is built accordingly. In this manner, a DTMF detection task is done following one-time detection computation. This proposal demonstrates an overall computational load reduction of 80.49% and 74.06% in comparison with a discrete Fourier transform (DFT) approach and the Goertzel algorithm, respectively. This detection complexity reduction is an advantage and an important issue for applying DTMF detection technique to embedded devices

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

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