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Method and system for automatically detecting morphemes in a task classification system using lattices

Method and system for automatically detecting morphemes in a task classification system using lattices description/claims

This application is a continuation application of U.S. patent application Ser. No. 10/158,082, filed May 31, 2002 and incorporated herein by reference in its entirety, which claims the benefit of U.S. Provisional Patent Application No. 60/322,447, filed Sep. 17, 2001, which is incorporated herein by reference in its entirety, and is also a continuation-in-part of U.S. patent applications Ser. Nos. 09/690,721 and 09/690,903 both filed Oct. 18, 2000, which claim priority from U.S. Provisional Application No. 60/163,838, filed Nov. 5, 1999. U.S. patent applications Ser. Nos. 09/690,721, 09/690,903, 11/420,082 and U.S. Provisional Application No. 60/163,838 are incorporated herein by reference in their entireties.

The invention relates to automated systems for communication recognition and understanding.

Conventional methods for constructing and training statistical models for recognition and understanding involve collecting and annotating large speech corpora for a task. This speech is manually transcribed and each utterance is then semantically labeled. The resultant database is exploited to train stochastic language models for recognition and understanding. These models are further adapted for different dialog states. Examples of such methods are shown in U.S. Pat. Nos. 5,675,707, 5,860,063, 6,044,337, 6,192,110, and 6,173,261, each of which is incorporated by reference herein in its entirety.

This transcription and labeling process is a major bottleneck in new application development and refinement of existing ones. For incremental training of a deployed automated dialog system, current technology would potentially require transcribing millions of transactions. This process is both time-consuming and prohibitively expensive.

The invention concerns a method and system for detecting morphemes in a user's communication. The method may include recognizing a lattice of phone strings from the user's input communication, the lattice representing a distribution over the phone strings, and detecting morphemes in the user's input communication using the lattice.

The morphemes may be acoustic and/or non-acoustic. The morphemes may represent any unit or sub-unit of communication including phones, diphones, phone-phrases, syllables, grammars, words, gestures, tablet strokes, body movements, mouse clicks, etc. The training speech may be verbal, non-verbal, a combination of verbal and non-verbal, or multimodal.

The invention is described in detail with reference to the following drawings wherein like numerals reference like elements, and wherein:

FIG. 1 is a block diagram of an exemplary task classification system;

FIG. 2 is a detailed block diagram of an exemplary morpheme generator;

FIG. 3 is a flowchart illustrating an exemplary morpheme generation process;

FIG. 4 is a flowchart illustrating an exemplary candidate phone-phrase selection process;

FIG. 5 is a flowchart of an exemplary task classification process;

FIG. 6 is a graph illustrating the number of recognized phones per utterance;

FIG. 7 is a graph illustrating the length comparison of recognized vs. transcribed utterances;

• Provisional Patent
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