Sparse reconstruction of quantized speech signals

Christoph Brauer, Dirk Lorenz, Timo Gerkmann

Abstract: We propose sparse reconstruction techniques to improve the quality and/or reduce the bit-rate of standard speech coders. To that end, we assume signal sparsity in some transform domain and formulate the problem of reconstructing the original signal in terms of constrained ℓ 1 -norm minimization. We use modern primal-dual methods in order to solve the resulting non-smooth convex optimization problem. Experiments show that with the proposed sparse reconstruction method the instrumentally predicted speech quality can be largely improved.