Invention Grant
- Patent Title: Cross-lingual discriminative learning of sequence models with posterior regularization
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Application No.: US14105973Application Date: 2013-12-13
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Publication No.: US09779087B2Publication Date: 2017-10-03
- Inventor: Dipanjan Das , Kuzman Ganchev
- Applicant: Google Inc.
- Applicant Address: US CA Mountain View
- Assignee: GOOGLE INC.
- Current Assignee: GOOGLE INC.
- Current Assignee Address: US CA Mountain View
- Agency: RMCK Law Group, PLC
- Main IPC: G06F17/27
- IPC: G06F17/27 ; G06F17/28

Abstract:
A computer-implemented method can include obtaining (i) an aligned bi-text for a source language and a target language, and (ii) a supervised sequence model for the source language. The method can include labeling a source side of the aligned bi-text using the supervised sequence model and projecting labels from the labeled source side to a target side of the aligned bi-text to obtain a labeled target side of the aligned bi-text. The method can include filtering the labeled target side based on a task of a natural language processing (NLP) system configured to utilize a sequence model for the target language to obtain a filtered target side of the aligned bi-text. The method can also include training the sequence model for the target language using posterior regularization with soft constraints on the filtered target side to obtain a trained sequence model for the target language.
Public/Granted literature
- US20150169549A1 CROSS-LINGUAL DISCRIMINATIVE LEARNING OF SEQUENCE MODELS WITH POSTERIOR REGULARIZATION Public/Granted day:2015-06-18
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