A speech error correction algorithm for natural language input processing

Abstract

Computerized processing of human speech input may be accomplished by 1) recognizing the phoneme sounds in the speech signals, 2) correctly identifying the words in each spoken sentence, 3) interpreting the meaning of the sentence, and 4) generating proper responses for each utterance. Individual speakers talk differently, and even an individual's enunciation patterns change with differing environments and discourse domains. These differences are called speaker idiosyncrasies. Regional speech dialects are included as a speaker idiosyncrasy. The source of such speaker differences has been identified as an individual's pronunciations of the vowel phonemes. Computerized speech processors treat these speaker idiosyncrasies as errors when the input phoneme sounds are unrecognizable. A generalized speech recognition system must accommodate such speech errors and, more particularly, ignore the speaker dependent pronunciations of phonemes. This implies that vowel phoneme pronunciations, the source of speaker idiosyncrasies and speech processing errors, should be overlooked during recognition of vocalized sentences. The research experiment consisted of construction of a system for identifying a natural language sentence using only speaker independent phonemes as the input. The motivating hypothesis for the experiment is that spoken sentences can be recognized from limited phoneme input. The research system accepts only strings of consonant phonemes, which are recognizable in a speaker independent environment. The original 'spoken' sentence is reproduced from the consonant phonemes and formatted as a word sequence for subsequent transmission to a natural language processing system. The system uses a vocabulary of general words and an expandable dictionary of domain specific words during the sentence reconstruction process. The research conclusions are that such a system can be built, and that the useful vocabulary must be expandable as the recognition system becomes more frequently used. The research system is intended as an interface between existing acoustic phoneme recognizers and existing natural language processors. The system accomplishes word recognition using only the consonant phonemes from continuous speech sentences, and generates word sequences in sentence form for output to an existing natural language processor. The domain specific vocabulary subsets used by the system facilitate its use as a sentence pre-processor especially with natural language understanding systems which rely on scripts, and the associated domain specific vocabularies, for semantic processing of topic oriented sentence groups.