f understanding spoken language, computers and super fast integrated circuits were not available. However, they managed to build the fundamental principles of speech recognition systems. Several approaches were used, each one with advantages and disadvantages. Two of these approaches are discussed below.Acoustic-Phonetic ApproachThe theory behind acoustic-phonetic approach is acoustic phonetics. This theory assumes that spoken language is divided into phonetic units that are finite and particular. These phonetic units are distinguished by properties that are apparent in the speech signal (7, pp.42-43). The process by which speech is recognised is described briefly in what follows: initially, speech is divided into segments. According to the acoustic properties of these segments, an appropriate phonetic unit is attached to it. The obtained sequence of units is used to formulate a valid word (7, p43). Figure 1: Phonetic sequence for a speech sample (7, 43).As an example, consider the sequence of phonetic units matched with a sample of speech illustrated in figure 1. The symbol ‘SIL’ indicates a silence whereas the vertical position of the phonetic unit indicates how good it is matched with the corresponding segment of speech (the higher, the best match). After searching, we can match the phonetic sequence SIL-AO-L-AX-B-AW-T with the expression ‘all about’. It is obvious that the chosen phonemes are not only the first choices in the phonetic sequence, but also second (B and AX) and third (L) choices. Therefore matching a phonetic sequence with a word or a group of words is not obvious (7, p.43). In fact, this the main disadvantage of this approach. Statistical Pattern Recognition ApproachIn statistical pattern recognition, the speech patterns are directly inputted into the system and compared with the patterns inputted in the system during training (7, p.43). Unlike th...
