Speech Segmentation - Lexical Segmentation

Lexical Segmentation

In all natural languages, the meaning of a complex spoken sentence (which often has never been heard or uttered before) can be understood only by decomposing it into smaller lexical segments (roughly, the words of the language), associating a meaning to each segment, and then combining those meanings according to the grammar rules of the language. The recognition of each lexical segment in turn requires its decomposition into a sequence of discrete phonetic segments and mapping each segment to one element of a finite set of elementary sounds (roughly, the phonemes of the language); the meaning then can be found by standard table lookup algorithms.

For most spoken languages, the boundaries between lexical units are surprisingly difficult to identify. One might expect that the inter-word spaces used by many written languages, like English or Spanish, would correspond to pauses in their spoken version; but that is true only in very slow speech, when the speaker deliberately inserts those pauses. In normal speech, one typically finds many consecutive words being said with no pauses between them, and often the final sounds of one word blend smoothly or fuse with the initial sounds of the next word.

Moreover, an utterance can have different meanings depending on how it is split into words. A popular example, often quoted in the field, is the phrase How to wreck a nice beach, which sounds very similar to How to recognize speech. As this example shows, proper lexical segmentation depends on context and semantics which draws on the whole of human knowledge and experience, and would thus require advanced pattern recognition and artificial intelligence technologies to be implemented on a computer.

This problem overlaps to some extent with the problem of text segmentation that occurs in some languages which are traditionally written without inter-word spaces, like Chinese and Japanese. However, even for those languages, text segmentation is often much easier than speech segmentation, because the written language usually has little interference between adjacent words, and often contains additional clues not present in speech (such as the use of Chinese characters for word stems in Japanese).