Fuzzy based natural speech concept system

• US 20040186704A1
• Filed: 12/11/2003
• Published: 09/23/2004
• Est. Priority Date: 12/11/2002
• Status: Abandoned Application

• Current Assignee: Voice Enabling Systems Technology Incorporated
• Original Assignee: Voice Enabling Systems Technology Incorporated
• Inventors: Basir, Otman A., Karray, Fakhreddine, Sun, Jiping
• Application Number:
  US10/733,168
• Publication Number:
  US 20040186704A1
• Time in Patent Office: Days
• US Class Current: 704/4
• CPC Class Codes: G06F 40/284 Lexical analysis, e.g. tokenisation or collocates

Abstract

A fuzzy natural speech concept system includes: (i) a concept classification, (ii) a fuzzy conceptual grammar learning, and (iii) a natural language concept derivation system. In the system, errors due to user input complexity and recognizer problem are compensated for because the broad context is measured as a fuzzy set to which a correct concept belongs. If used in an automatic telephone conversation system, the fuzzy natural speech concept system will provide enough information about the intentions of the user as to take the most appropriate action to provide useful information and service to the user.

Claims

1. A concept classification system that classifies concepts for a domain according to the statistical significance of these concepts in the domain comprising:

at least one general semantic lexicon, implemented as a computational database and accessible by the software modules of the classification system;

at least one text corpus, containing texts specific for a domain for an application of a telephone conversation system, implemented as a computational database; and

a statistical inference algorithm, which makes use of distributional patterns of words in the corpus, together with their conceptual categories in the general semantic lexicon, to derive significant concepts of a particular domain.

2. A fuzzy grammar rule derivation system to learn fuzzy grammar from corpora comprising:

a shallow parsing algorithm, which assigns syntactic categories to words and segments a sentence into syntactic phrases;

a syntactic weight assignment algorithm, which assigns syntactic weight to context vectors according to their relative importance to a concept; and

a statistical parameter calculation algorithm, which assigns frequency and differentiation parameters to context vectors of concepts.

3. A concept derivation system, which applies fuzzy grammar rules to a sentence to derive the intended meanings of the speaker comprising:

a matching algorithm to match words to possible multiple concepts, as described in the fuzzy grammar;

a fuzzy inference algorithm which applies fuzzy grammar rules to the context vector of a possible concept and assigns a membership degree to the concept;

an evaluation algorithm, which examines the test results of the fuzzy grammar rule engine and the inference engine to decide if further training of the system is needed or the system has passed the requirement for delivery as the natural language understanding component of a telephone conversation system.