Unsupervised and active learning in automatic speech recognition for call classification

Patent №

US 8,818,808

Granted

2014-08-26

Filed 2005

Owner

AT&T CORP.

+2 more

Lab

AI components

5

ml · nlp · speech · kr · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

11063910

Utterance data that includes at least a small amount of manually transcribed data is provided. Automatic speech recognition is performed on ones of the utterance data not having a corresponding manual transcription to produce automatically transcribed utterances. A model is trained using all of the manually transcribed data and the automatically transcribed utterances. A predetermined number of utterances not having a corresponding manual transcription are intelligently selected and manually transcribed. Ones of the automatically transcribed data as well as ones having a corresponding manual transcription are labeled. In another aspect of the invention, audio data is mined from at least one source, and a language model is trained for call classification from the mined audio data to produce a language model.

AI classification

Speech1.00
Natural language1.00
Machine learning1.00
AI hardware0.68
Knowledge representation0.66
Vision0.39
Planning0.01
Evolutionary computation0.00

Ownership

AT&T CORP.

assignment · 163380761

AT&T PROPERTIES, LLC

assignment · 351410045

AT&T INTELLECTUAL PROPERTY II, L.P.

assignment · 351410149

Assignors

HAKKANI-TUR, DILEK Z., RAHIM, MAZIN G., RICCARDI, GIUSEPPE, TUR, GOKHAN

On an employer assignment, the assignors are typically the inventors.

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