Waveform coding for low-power digital filtering of speech data

This paper evaluates waveform coding techniques known from low bit-rate communication for their usefulness in low-power digital FIR filtering of speech signals. The encodings considered include linear PCM, PCM with adaptive and logarithmic quantization, and differential PCM, combined with two’s-complement and sign-magnitude number representation. Selected implementation aspects for each alternative are discussed. Experimental results are presented to quantify potential power savings subject to statistical signal properties and operating conditions. Guidelines for the choice of encoding in application-specific digital signal processing of speech data are provided.