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公开(公告)号：US20190244600A1
公开(公告)日：2019-08-08
申请号：US16388753
申请日：2019-04-18
申请人： SoundHound, Inc.
IPC分类号： G10L15/02 , G06N20/00 , H04L29/08 , G10L25/90 , G10L15/06 , G06Q30/02 , G06F17/27 , G10L15/18
CPC分类号： G10L15/02 , G06F17/2705 , G06F17/271 , G06F17/274 , G06N20/00 , G06Q30/0251 , G06Q30/0276 , G06Q30/0277 , G10L15/063 , G10L15/1815 , G10L15/22 , G10L15/26 , G10L25/51 , G10L25/90 , G10L2015/025 , H04L67/306
摘要： A method is provided for advertisement selection. The method includes recognizing words from user speech over a large number of interactions, computing a number of unique words uttered during the interactions, classifying the user by the number of unique words uttered during the interactions, and selecting an advertisement targeted to the classified users.
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公开(公告)号：US20190205372A1
公开(公告)日：2019-07-04
申请号：US15860362
申请日：2018-01-02
申请人： Facebook, Inc.
发明人： Xian Li , Irina-Elena Veliche , Debnil Sur , Shaomei Wu , Amit Bahl , Juan Miguel Pino
CPC分类号： G06F17/273 , G06F3/0481 , G06F17/24 , G06F17/274 , G06N20/00
摘要： In one embodiment, a method includes identifying a plurality of dyslexic users on an online social network. The plurality of dyslexic users may be identified based on content objects posted by these users over a particular time period, where the content objects may include one or more of word-level errors or sentence-level errors. A machine-learning model may be trained for text correction using a corpus of social network data, which may include at least the content objects with one or more of word-level errors or sentence-level errors, and a corresponding set of corrected content objects. A text string including one or more errors may be received from a client system associated with a first user. The text string may be transformed into a vector representation using an encoder of the machine-learning model. A corrected text string may be generated from the vector representation using a decoder of the machine-learning model.
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公开(公告)号：US20190197120A1
公开(公告)日：2019-06-27
申请号：US15854073
申请日：2017-12-26
发明人： Pranay Lohia , Saket Gurukar , Rishabh Gupta , Himanshu Gupta
CPC分类号： G06F17/2881 , G06F17/274 , G06F17/2765 , G06F17/278 , G06F17/2785 , G06N5/022 , G06N20/00
摘要： Methods, systems, and computer program products for automatically suggesting a temporal opportunity for writing one or more sequel articles via artificial intelligence are provided herein. A computer-implemented method includes extracting one or more types of information from a prior written document; automatically determining, based on the extracted information, at least one temporal opportunity for generating a follow-up written document to the prior written document; automatically generating a follow-up written document to the prior written document, the follow-up written document being written in a style that indicates that it is in response to the prior written document, in accordance with the at least one determined temporal opportunity, and based on (i) one or more items of information, related to the extracted information, derived from one or more web sources, and (ii) a writing model attributed to a user.
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公开(公告)号：US20190019503A1
公开(公告)日：2019-01-17
申请号：US16136959
申请日：2018-09-20
申请人： ASAPP, INC.
发明人： Shawn Henry
CPC分类号： G10L15/197 , G06F17/2715 , G06F17/274 , G06F17/277 , G06F17/2775 , G06F17/289 , G06N3/02 , G06N3/0445 , G06N3/0472 , G06N3/08 , G06N20/10 , G10L15/14 , G10L15/148 , G10L15/16 , G10L15/22 , G10L15/30
摘要： A language model may be used in a variety of natural language processing tasks, such as speech recognition, machine translation, sentence completion, part-of-speech tagging, parsing, handwriting recognition, or information retrieval. A natural language processing task may use a vocabulary of words, and a word hash vector may be created for each word in the vocabulary. A sequence of input words may be received, and a hash vector may be obtained for each word in the sequence. A language model may process the hash vectors for the sequence of input words to generate an output hash vector that describes words that are likely to follow the sequence of input words. One or words may then be selected using the output word hash vector and used for a natural language processing task.
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公开(公告)号：US20190019501A1
公开(公告)日：2019-01-17
申请号：US16135885
申请日：2018-09-19
申请人： Google LLC
发明人： Matthew Sharifi , Jakob Foerster
CPC分类号： G10L13/043 , G06F17/274 , G06F17/2775 , G10L13/08
摘要： In some implementations, a language proficiency of a user of a client device is determined by one or more computers. The one or more computers then determines a text segment for output by a text-to-speech module based on the determined language proficiency of the user. After determining the text segment for output, the one or more computers generates audio data including a synthesized utterance of the text segment. The audio data including the synthesized utterance of the text segment is then provided to the client device for output.
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公开(公告)号：US20180365219A1
公开(公告)日：2018-12-20
申请号：US15623613
申请日：2017-06-15
发明人： Aysu Ezen Can , Roberto DeLima , Corville Allen
CPC分类号： G06F17/2785 , G06F17/2705 , G06F17/274 , G06F17/278 , G06N5/043
摘要： According to one embodiment, a method, computer system, and computer program product for natural language processing is provided. The present invention may include detecting natural language entities, and running parsing algorithms on the natural language entities to determine the relationship between said natural language entities. The present invention may further comprise assigning, by the parsing algorithms, initial scores to detected natural language entities based on the relationship between said natural language entities; choosing a final score for plurality of natural language entities; and comparing the final score against a threshold to determine whether the natural language entities are within the same context.
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公开(公告)号：US20180359198A1
公开(公告)日：2018-12-13
申请号：US15618842
申请日：2017-06-09
申请人： Google Inc.
发明人： Laura Eidem , Alex Jacobson
CPC分类号： H04L51/02 , G06F3/16 , G06F17/271 , G06F17/274 , G06F21/6218 , G10L13/08 , H04L67/306
摘要： Modifying computer program output in a voice or non-text input activated environment is provided. A system can receive audio signals detected by a microphone of a device. The system can parse the audio signal to identify a computer program to invoke. The computer program can identify a dialog data structure. The system can modify the identified dialog data structure to include a content item. The system can provide the modified dialog data structure to a computing device for presentation.
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公开(公告)号：US20180330231A1
公开(公告)日：2018-11-15
申请号：US15591235
申请日：2017-05-10
发明人： Yu Gu , Dingcheng Li , Kai Liu , Su Liu
CPC分类号： G06N3/08 , G06F17/271 , G06F17/274 , G06F17/277 , G06F17/278 , G06F17/2785 , G06F17/5009 , G06F19/321 , G16H10/60 , G16H50/50
摘要： Disclosed aspects relate to entity model establishment using an infinite mixture topic modeling (IMTM) technique. A set of event data which corresponds to a set of events may be detected. Using the IMTM technique, the set of event data which corresponds to the set of events may be analyzed. Based on analyzing the set of event data using the IMTM technique, a set of entity models for the set of events may be determined. Based on the set of entity models for the set of events, a subset of the set of entity models for the set of events may be established.
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公开(公告)号：US20180321931A1
公开(公告)日：2018-11-08
申请号：US16031673
申请日：2018-07-10
CPC分类号： G06F8/65 , G06F8/71 , G06F15/18 , G06F17/274 , G06F17/2785 , G06N99/005
摘要： A method and system are provided. The method includes generating, by a machine-based sentiment prediction generator, respective machine-determined sentiment predictions for each of a plurality of software patches using sentiment analysis. The method further includes setting, by a sentiment-based confidence value generator, a confidence value for each of the plurality of software patches based on the machine-determined sentiment predictions. The method also includes at least one of selecting and prioritizing, by a software patch selector and prioritizer, at least one of the plurality of software patches based on the respective confidence value therefor.
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公开(公告)号：US20180285345A1
公开(公告)日：2018-10-04
申请号：US15478769
申请日：2017-04-04
CPC分类号： G06F17/2785 , G06F17/2705 , G06F17/2735 , G06F17/274 , G06F17/277 , G10L15/26 , G10L15/265
摘要： Aspects of the disclosure relate to using a natural language processing system to analyze mobile application feedback. A computing platform having at least one processor, a memory, and a communication interface may receive mobile application feedback information comprising text feedback associated with feedback of a mobile application. The computing platform may identify one or more nouns associated with the text feedback. The computing platform may identify one or more text feedback topics. The computing platform may generate one or more commands directing a sentiment analysis server to determine one or more sentiments for the one or more text feedback topics. The computing platform may transmit the one or more commands directing the sentiment analysis server to determine the one or more sentiments. The computing platform may receive the one or more sentiments. The computing platform may transmit the feedback topics and the one or more sentiments.
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