Invention Grant
- Patent Title: Model shrinking for embedded keyword spotting
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Application No.: US14751975Application Date: 2015-06-26
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Publication No.: US09600231B1Publication Date: 2017-03-21
- Inventor: Ming Sun , Björn Hoffmeister , Shiv Naga Prasad Vitaladevuni , Varun Kumar Nagaraja
- Applicant: Amazon Technologies, Inc.
- Applicant Address: US WA Seattle
- Assignee: AMAZON TECHNOLOGIES, INC.
- Current Assignee: AMAZON TECHNOLOGIES, INC.
- Current Assignee Address: US WA Seattle
- Agency: Seyfarth Shaw LLP
- Agent Ilan N. Barzilay; Tyrus S. Cartwright
- Main IPC: G10L15/18
- IPC: G10L15/18 ; G06F3/16 ; G10L15/02 ; G10L15/06 ; G10L15/22

Abstract:
A revised support vector machine (SVM) classifier is offered to distinguish between true keywords and false positives based on output from a keyword spotting component of a speech recognition system. The SVM operates on a reduced set of feature dimensions, where the feature dimensions are selected based on their ability to distinguish between true keywords and false positives. Further, support vectors pairs are merged to create a reduced set of re-weighted support vectors. These techniques result in an SVM that may be operated using reduced computing resources, thus improving system performance.
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