A nonuniform sampling technique based on inflection point detection and its application to speech coding.

Abstract

In order to reduce the data amount, the nonuniform sampling (NUS) method detects samples of a signal, such as local maxima and minima. To overcome the sparseness problem of the NUS method, an inflection point detection (IPD) method is proposed to sample a signal nonuniformly. The IPD samples a signal not only at the local maxima and minima, but also at the inflection points where the slope of the signal changes. To show its usefulness, the IPD is applied to speech coding. The encoder transmits the time instants and sample amplitude values of the inflection points. At the receiver, the decoder estimates the sample amplitude values at the noninflection points by interpolating the received information. Simulation results show that the IPD method produces 7% mean square error improvement over the NUS method. With a small threshold to detect inflection points, the proposed coding method shows 0.38-8.72 dB signal-to-noise ratio (SNR) and 0.5-1.3 mean opinion score improvement, compared to the continuously variable slope delta modulation algorithm (CVSDM). The IPD method produces up to 8.5 dB improvement in SNR over the CVSDM at bit error rates (BER) below 5 × 10(-5), while the IPD method becomes worse than the CVSDM at BER above 5 × 10(-5).