DIGITAL SPEECH PROCESSING



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I. Introduction

Speech is the most sophisticated signal naturally produced by humans The speech signal carries linguistic information for sharing of information and ideas. It allows people to express emotions and verbally share feelings. It is the most fundamental form of communication among humans. The aim of digital speech processing is to take advantage of digital computing techniques to process the speech signal for increased understanding, improved communication, and increased efficiency and productivity associated with speech activities.
The field of speech processing includes speech analysis and representation, speech coding, speech synthesis, speech recognition and understanding, speaker verification, and speech enhancement. Speech is a complex signal that is characterized by varying distributions of energy in time as well as in frequency, depending on the specific sound that is being produced. The speech signal also possesses other characteristics that make it a very efficient means for carrying semantic (meaning) as well as pragmatic (task-dependent) information. The processes of speech analysis and representation, which lie at the technical basis of digital speech processing, attempt to use computational algorithms to “discover”, to measure, and to represent the important properties of speech for many applications.



II. Speech Analysis and Representations

The traditional framework for analyzing speech is the source-tract model first proposed by Homer Dudley at Bell Laboratories in the 1930s. In this model, as depicted in Figure 1, a speech excitation signal is produced by an excitation source and processed by a filter system that “modulates” the spectral characteristics of the excitation signal based on the shape of the vocal tract for the specific sound being generated. The excitation source has two components - a ”buzz” source and a “hiss” source.



Speech Coding

The goal of speech coding is to transform the speech waveform into a digital representation so as to allow efficient transmission and storage of the signal. The transformation, in general, will result in a certain loss of fidelity and hence, the efficiency of the speech coder is measured in terms of the required bit rate to achieve a certain quality requirement. The higher the bit rate, the easier it is to preserve the quality. Besides quality, a related dimension of significance is the incurred delay during processing. For real-time telephony between humans, a delay (processing plus transmission) of over 200 ms would make fluent two-way communication quite difficult. To achieve high coding efficiency, however, one needs to take advantage of the slow-varying nature of speech; as a result, many coding algorithms use a long delay buffer on the order of a few centiseconds to meet the efficiency requirements. Trade-offs among the three coding dimensions – bit-rate, quality, and delay – often have to be made in specific applications.



Speech Synthesis
Modern speech synthesis is the product of a rich history of attempts to generate speech by mechanical means. The earliest known device to mimic human speech was constructed by Wolfgang von Kempelen over two hundred years ago. His machine consisted of elements that mimicked various organs used by humans to produce speech – a bellows for the lungs, a tube for the vocal tract, a side branch for the nostrils, etc. Interest in such mechanical analogs of the human vocal apparatus continued well into the twentieth century. In the latter half of the nineteenth century, Helmholz and others began synthesizing vowels and other sonorants by superposition of harmonic waveforms with appropriate amplitudes.