Generating a task-adapted acoustic model from one or more different corpora
US7006972B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Mar 20, 2002 |
| Grant date | Feb 28, 2006 |
| Priority date | — |
| Expiry date | Jul 10, 2024 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L15/183
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.