Time-domain algorithms for harmonic bandwidth reduction and time scaling of speech signals

Abstract

Frequency scaling of speech signals by methods based on short-time Fourier analysis (STFA), analytic rooting, and harmonic compression using a bank of filters, is a complex operation which requires a large amount of computation in a digital implementation. It is shown in this paper that, by incorporating pitch frequency information into a frequency-scaling process based on STFA, it is possible, to a good approximation, to perform this operation in the time domain with very few arithmetic operations (one multiplication and two additions per output sample, in most applications). The derivation of the time-domain harmonic scaling (TDHS) algorithms, selection of parameters, and, in particular, the determination of an appropriate weighting function used in the algorithms, as well as several potential applications, are detailed in the paper. Two proposed applications are discussed in greater detail. These are 1) a vocoder system which incorporates waveform coding of the frequency divided signal (by a factor of up to 3), and 2) a computer-based isolated-word recognition system in which all input utterances are compressed to the same duration at the preprocessing phase effecting an overall computation reduction by a factor of up to 3. Computer simulation results which demonstrate the TDHS algorithms' performance are included.