Long D Nguyen

US Patent:

56218591, Apr 15, 1997

Filed:

Jan 19, 1994

Appl. No.:

8/183719

Inventors:

Richard M. Schwartz - Sudbury MA
Long Nguyen - Medford MA

Assignee:

BBN Corporation - Cambridge MA

International Classification:

G10L 506
G10L 900

US Classification:

395 265

Abstract:

The invention provides a method of large vocabulary speech recognition that employs a single tree-structured phonetic hidden Markov model (HMM) at each frame of a time-synchronous process. A grammar probability is utilized upon recognition of each phoneme of a word, before recognition of the entire word is complete. Thus, grammar probabilities are exploited as early as possible during recognition of a word. At each frame of the recognition process, a grammar probability is determined for the transition from the most likely preceding grammar state to a set of words that share at least one common phoneme. The grammar probability is combined with accumulating phonetic evidence to provide a measure of the likelihood that a state in the HMM will lead to the word most likely to have been spoken. In a preferred embodiment, phonetic context information is exploited, even before the complete context of a phoneme is known. Instead of an exact triphone model, wherein the phonemes previous and subsequent to a phoneme are considered, a composite triphone model is used that exploits partial phonetic context information to provide a phonetic model that is more accurate than aphonetic model that ignores context.