A speech recognition system for connected word sequences

The Speech Communications Group at SPERRY UNIVAC Defense Systems is developing a linguistically-oriented procedure for recognizing words, phrases, and natural sentences by computer. The major components of the current speech recognition system perform acoustic and phonetic analysis, phonetic segmentation, and lexical matching and scoring. The acoustic processing is based on a linear-predictive spectral analysis of the speech signal. Sounds are classified by manner, place, and voicing using formant frequencies and other spectral functions, as well as information about syllable boundaries and nuclei. A linear sequence of analysis segments is created, and matched against the lexicon using a scoring matrix that ranks analysis-lexical segment pairs by their expected confusions. Word sequences are progressively formed and ranked against the entire input to determine the most likely phrases spoken. When the recognition system was tested on a 31-word vocabulary from two male speakers, single word recognition scores of 95% correct were obtained when the task syntax was used. Preliminary results for recognizing connected word sequences from three male speakers range from 54 to 74% for a task with constrained word order. Current plans for enhancing the recognition system include the incorporation of components for phonological rules, speaker normalization, and prosodic guidelines. By adding more powerful procedures for syntactic and semantic analysis, the system will be extended from the recognition of several-word noun phrases to the understanding of more natural sentences.