An Introduction to Signal Processing for Speech

The formal tools of signal processing emerged in the mid twentieth century when electronics gave us the ability to manipulate signals — time-varying measurements — to extract or rearrange various aspects of interest to us, i.e., the information in the signal. The core of traditional signal processing is a way of looking at the signals in terms of sinusoidal components of differing frequencies (the Fourier domain), and a set of techniques for modifying signals that are most naturally described in that domain, i.e., filtering. Although originally developed using analog electronics, since the 1970s signal processing has more and more been implemented on computers in the digital domain, leading to some modifications to the theory without changing its essential character. This chapter aims to give a transparent and intuitive introduction to the basic ideas of the Fourier domain and filtering, and connects them to some of the common representations used in speech science, including the spectrogram and cepstral coefficients. We assume the absolute minimum of prior technical background, which will naturally be below the level of many readers; however, there may be some value in taking such a ground-up approach even for those for whom much of the material is review