05621859 is referenced by 248 patents and cites 7 patents.

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. In another preferred embodiment, the single phonetic tree method is used as the forward pass of a forward/backward recognition process, wherein the backward pass employs a recognition process other than the single phonetic tree method.

Title
Single tree method for grammar directed, very large vocabulary speech recognizer
Application Number
8/183719
Publication Number
5621859
Application Date
January 19, 1994
Publication Date
April 15, 1997
Inventor
Long Nguyen
Medford
MA, US
Richard M Schwartz
Sudbury
MA, US
Agent
Lappin & Kusmer
Assignee
BBN Corporation
MA, US
IPC
G10L 9/00
G10L 5/06
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