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
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.