Invention Grant
US08935167B2 Exemplar-based latent perceptual modeling for automatic speech recognition
有权
用于自动语音识别的基于示例的潜在感知建模
- Patent Title: Exemplar-based latent perceptual modeling for automatic speech recognition
- Patent Title (中): 用于自动语音识别的基于示例的潜在感知建模
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Application No.: US13626825Application Date: 2012-09-25
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Publication No.: US08935167B2Publication Date: 2015-01-13
- Inventor: Jerome Bellegarda
- Applicant: Apple Inc.
- Applicant Address: US CA Cupertino
- Assignee: Apple Inc.
- Current Assignee: Apple Inc.
- Current Assignee Address: US CA Cupertino
- Agency: Morrison & Foerster LLP
- Main IPC: G10L15/00
- IPC: G10L15/00 ; G10L15/06

Abstract:
Methods, systems, and computer-readable media related to selecting observation-specific training data (also referred to as “observation-specific exemplars”) from a general training corpus, and then creating, from the observation-specific training data, a focused, observation-specific acoustic model for recognizing the observation in an output domain are disclosed. In one aspect, a global speech recognition model is established based on an initial set of training data; a plurality of input speech segments to be recognized in an output domain are received; and for each of the plurality of input speech segments: a respective set of focused training data relevant to the input speech segment is identified in the global speech recognition model; a respective focused speech recognition model is generated based on the respective set of focused training data; and the respective focused speech recognition model is provided to a recognition device for recognizing the input speech segment in the output domain.
Public/Granted literature
- US20140088964A1 Exemplar-Based Latent Perceptual Modeling for Automatic Speech Recognition Public/Granted day:2014-03-27
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