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
  • Application No.: US13626825
    Application Date: 2012-09-25
  • Publication No.: US08935167B2
    Publication 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
Exemplar-based latent perceptual modeling for automatic speech recognition
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.
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