An algorithm for the training of CELP excitation codebooks

CELP schemes with trained excitation codebook are able to reproduce more complex waveforms than stochastic CELP schemes. Here we present a new algorithm for the design of trained CELP excitation code-books which are well adapted to the residual of speech even in transition regions. The vectors of the excitation codebook are adapted to a training speech sequence by applying an iterative algorithm. To obtain a high coding accuracy, the analysis-by-synthesis error measure used during coding process is also used in the codebook design procedure. Due to the simultaneous occurance of quantized amplitude vector and quantized gain in the error measure, both codebooks are optimized iteratively. The amplitude codebook vectors are designed as sub-vectors of a so-called base excitation sequence by shifting their offset. Comparative listening tests have shown that this method outperforms stochastic CELP in objective SNR as well as in subjective quality.