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公开(公告)号:US09911437B2
公开(公告)日:2018-03-06
申请号:US15146283
申请日:2016-05-04
IPC分类号: G10L15/00 , G10L25/51 , G10L15/19 , G10L17/04 , G10L15/18 , G06F3/16 , G10L15/05 , G10L15/07 , G10L15/30 , G10L15/183
CPC分类号: G10L25/51 , G06F3/162 , G10L15/05 , G10L15/07 , G10L15/18 , G10L15/183 , G10L15/19 , G10L15/30 , G10L17/04 , G10L2015/228
摘要: Disclosed herein are systems, methods, and computer-readable storage media for improving speech recognition accuracy using textual context. The method includes retrieving a recorded utterance, capturing text from a device display associated with the spoken dialog and viewed by one party to the recorded utterance, and identifying words in the captured text that are relevant to the recorded utterance. The method further includes adding the identified words to a dynamic language model, and recognizing the recorded utterance using the dynamic language model. The recorded utterance can be a spoken dialog. A time stamp can be assigned to each identified word. The method can include adding identified words to and/or removing identified words from the dynamic language model based on their respective time stamps. A screen scraper can capture text from the device display associated with the recorded utterance. The device display can contain customer service data.
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12.
公开(公告)号:US09734820B2
公开(公告)日:2017-08-15
申请号:US14080361
申请日:2013-11-14
CPC分类号: G10L15/005 , G06F17/2775 , G06F17/289 , G10L13/00 , G10L15/04 , G10L15/26
摘要: A system, method and computer-readable storage device which balance latency and accuracy of machine translations by segmenting the speech upon locating a conjunction. The system, upon receiving speech, will buffer speech until a conjunction is detected. Upon detecting a conjunction, the speech received until that point is segmented. The system then continues performing speech recognition on the segment, searching for the next conjunction, while simultaneously initiating translation of the segment. Upon translating the segment, the system converts the translation to a speech output, allowing a user to hear an audible translation of the speech originally heard.
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公开(公告)号:US09727557B2
公开(公告)日:2017-08-08
申请号:US15212944
申请日:2016-07-18
CPC分类号: G06F17/28 , G06F17/21 , G06F17/27 , G06F17/2705 , G06F17/2715 , G06F17/2735 , G06F17/2765 , G10L2015/0633
摘要: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for collecting web data in order to create diverse language models. A system configured to practice the method first crawls, such as via a crawler operating on a computing device, a set of documents in a network of interconnected devices according to a visitation policy, wherein the visitation policy is configured to focus on novelty regions for a current language model built from previous crawling cycles by crawling documents whose vocabulary considered likely to fill gaps in the current language model. A language model from a previous cycle can be used to guide the creation of a language model in the following cycle. The novelty regions can include documents with high perplexity values over the current language model.
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公开(公告)号:US09720907B2
公开(公告)日:2017-08-01
申请号:US14853053
申请日:2015-09-14
发明人: Srinivas Bangalore , Sumit Chopra
IPC分类号: G06F17/28
CPC分类号: G06F17/28
摘要: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for learning latent representations for natural language tasks. A system configured to practice the method analyzes, for a first natural language processing task, a first natural language corpus to generate a latent representation for words in the first corpus. Then the system analyzes, for a second natural language processing task, a second natural language corpus having a target word, and predicts a label for the target word based on the latent representation. In one variation, the target word is one or more word such as a rare word and/or a word not encountered in the first natural language corpus. The system can optionally assigning the label to the target word. The system can operate according to a connectionist model that includes a learnable linear mapping that maps each word in the first corpus to a low dimensional latent space.
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公开(公告)号:US09703769B2
公开(公告)日:2017-07-11
申请号:US14877272
申请日:2015-10-07
CPC分类号: G06F17/2705 , G06F17/218 , G06F17/27 , G06F17/2775 , G10L15/05 , G10L15/26 , G10L2015/025 , G10L2015/081 , G10L2015/088
摘要: A clausifier and method of extracting clauses for spoken language understanding are disclosed. The method relates to generating a set of clauses from speech utterance text and comprises inserting at least one boundary tag in speech utterance text related to sentence boundaries, inserting at least one edit tag indicating a portion of the speech utterance text to remove, and inserting at least one conjunction tag within the speech utterance text. The result is a set of clauses that may be identified within the speech utterance text according to the inserted at least one boundary tag, at least one edit tag and at least one conjunction tag. The disclosed clausifier comprises a sentence boundary classifier, an edit detector classifier, and a conjunction detector classifier. The clausifier may comprise a single classifier or a plurality of classifiers to perform the steps of identifying sentence boundaries, editing text, and identifying conjunctions within the text.
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