GENERATING A TASK-ADAPTED ACOUSTIC MODEL FROM ONE OR MORE DIFFERENT CORPORA

Patent №

US 7,006,972

Granted

2006-02-28

Filed 2002

Owner

MICROSOFT CORPORATION

AI components

7

ml · nlp · vision · speech · kr · planning · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

10103642

The present invention generates a task-dependent acoustic model from a supervised task-independent corpus and further adapted it with an unsupervised task dependent corpus. The task-independent corpus includes task-independent training data which has an acoustic representation of words and a sequence of transcribed words corresponding to the acoustic representation. A relevance measure is defined for each of the words in the task-independent data. The relevance measure is used to weight the data associated with each of the words in the task-independent training data. The task-dependent acoustic model is then trained based on the weighted data for the words in the task-independent training data.

AI classification

Natural language1.00
Speech1.00
Machine learning1.00
Planning1.00
AI hardware1.00
Knowledge representation1.00
Vision0.98
Evolutionary computation0.00

Ownership

MICROSOFT CORPORATION

assignment · 127360047

Assignors

HWANG, MEI YUH

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

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