Code-excited linear prediction(CELP): High-quality speech at very low bit rates

TLDR

The authors propose a CELP speech coder that selects the optimal innovation sequence from a codebook to maximize fidelity and compare different codebooks for effectiveness. The coder processes 8‑kHz speech in 5‑ms blocks of 40 samples, each block chosen from 1,024 possible innovation sequences, and applies two time‑varying linear recursive filters—one with a long‑delay pitch predictor and one with a short‑delay spectral envelope predictor—to each innovation sample, yielding a 0.25‑bit‑per‑sample rate. Experiments show that a random codebook provides a slight speech‑quality advantage over deterministic codebooks at low bit rates.

Abstract

We describe in this paper a code-excited linear predictive coder in which the optimum innovation sequence is selected from a code book of stored sequences to optimize a given fidelity criterion. Each sample of the innovation sequence is filtered sequentially through two time-varying linear recursive filters, one with a long-delay (related to pitch period) predictor in the feedback loop and the other with a short-delay predictor (related to spectral envelope) in the feedback loop. We code speech, sampled at 8 kHz, in blocks of 5-msec duration. Each block consisting of 40 samples is produced from one of 1024 possible innovation sequences. The bit rate for the innovation sequence is thus 1/4 bit per sample. We compare in this paper several different random and deterministic code books for their effectiveness in providing the optimum innovation sequence in each block. Our results indicate that a random code book has a slight speech quality advantage at low bit rates. Examples of speech produced by the above method will be played at the conference.