IP Library Granted Patent US 7,181,399
Granted Patent B1
US 7,181,399 · App. 09/314,637 · Granted Feb 20, 2007

Recognizing the numeric language in natural spoken dialogue

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Quick Facts
Patent No.
US 7,181,399
App. No.
09/314,637
Granted
Feb 20, 2007
Kind
B1
Abstract

A system for recognizing connected digits in natural spoken dialogue includes a speech recognition processor that receives unconstrained fluent input speech and produces a string of words that can include a numeric language, and a numeric understanding processor that converts the string of words into a sequence of digits based on a set of rules. An acoustic model database utilized by the speech recognition processor includes a first set of hidden Markov models that characterize the acoustic features of numeric words and phrases, a second set of hidden Markov models that characterize the acoustic features of the remaining vocabulary words, and a filler model that characterizes the acoustic features of out-of-vocabulary utterances. An utterance verification processor verifies the accuracy of the string of words. A validation database stores a grammar, and a string validation processor outputs validity information based on a comparison of the sequence of digits with the grammar. A dialogue manager processor initiates an action based on the validity information.

Claims (21)

1. A speech recognition method, comprising:

receiving a speech signal;

performing a speech recognition process on the received speech signal to produce speech recognition results, the speech recognition process being based on a set of acoustical models that has been defined for a numeric language, wherein the numeric language includes a subset of a vocabulary, the subset of the vocabulary including words that identify digits in number strings and words that enable the interpretation and understanding of number strings; and

generating a sequence of digits using said speech recognition results, said generating being based on a set of rules, wherein

the numeric language includes digits, natural numbers, alphabets, re-starts, and city/country name classes.

2. The method of claim 1 , wherein the acoustical models are hidden Markov models.

3. The method of claim 1 , wherein said generating is implemented by a numeric understanding processor.

4. The method of claim 1 , wherein the set of rules includes one of a naturals rule and alphabets rule.

5. The method of claim 1 , wherein the set of rules includes a restarts rule.

6. The method of claim 1 , wherein the set of rules includes a city/country rule.

7. The method of claim 1 , wherein the set of rules includes a numeric phrases rule that realigns digits.

8. The method of claim 1 , wherein said performing is implemented by a speech recognition processor.

9. The method of claim 1 , wherein said performing is further based on a second set of acoustical models that has been defined for other words in the vocabulary.

10. The method of claim 9 , wherein said second set of acoustical models is defined at a quality level different than the set of acoustical models for the numeric language.

11. A system comprising:

a speech recognition processor that receives unconstrained input speech and outputs a string of words, the speech recognition processor being based on a numeric language that represents a subset of a vocabulary, the subset including a set of words identified as being relevant for interpreting and understanding number strings;

a numeric understanding processor containing classes of rules for converting the string of words into a sequence of digits;

an acoustic model database utilized by the speech recognition processor;

a validation database that stores a set of valid numbers; and

a string validation processor that outputs validity information based on a comparison of a sequence of digits output by the numeric understanding processor with valid numbers in the validation database, wherein

said numeric language includes digits, natural numbers, alphabets, re-starts, and city/country name phrase classes.

Assignments (4)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 26, 2017
From: AT&T INTELLECTUAL PROPERTY II, L.P.
To: NUANCE COMMUNICATIONS, INC.
Reel/Frame 041498/0316 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 12, 2017
From: BUNTSCHUH, BRUCE MELVIN
To: AT&T CORP.
Reel/Frame 040956/0358 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 28, 2016
From: AT&T CORP.
To: AT&T PROPERTIES, LLC
Reel/Frame 038274/0841 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 28, 2016
From: AT&T PROPERTIES, LLC
To: AT&T INTELLECTUAL PROPERTY II, L.P.
Reel/Frame 038274/0917 →