Invention Grant
- Patent Title: Automatic learning of language models
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Application No.: US15483977Application Date: 2017-04-10
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Publication No.: US10535342B2Publication Date: 2020-01-14
- Inventor: Christian Liensberger
- Applicant: Microsoft Technology Licensing, LLC
- Applicant Address: US WA Redmond
- Assignee: Microsoft Technology Licensing, LLC
- Current Assignee: Microsoft Technology Licensing, LLC
- Current Assignee Address: US WA Redmond
- Main IPC: G10L15/18
- IPC: G10L15/18 ; G10L15/22 ; G06F17/27 ; G10L15/183 ; G10L15/193

Abstract:
Techniques and systems are disclosed for context-dependent speech recognition. The techniques and systems described enable accurate recognition of speech by accessing sub-libraries associated with the context of the speech to be recognized. These techniques translate audible input into audio data at a smart device and determine context for the speech, such as location-based, temporal-based, recipient-based, and application based context. The smart device then accesses a context-dependent library to compare the audio data with phrase-associated translation data in one or more sub-libraries of the context-dependent library to determine a match. In this way, the techniques allow access to a large quantity of phrases while reducing incorrect matching of the audio data to translation data caused by organizing the phrases into context-dependent sub-libraries.
Public/Granted literature
- US20180293977A1 Automatic Learning of Language Models Public/Granted day:2018-10-11
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