公开(公告)号：US20180261216A1

公开(公告)日：2018-09-13

申请号：US15456354

申请日：2017-03-10

Applicant: SoundHound, Inc.

Inventor： Rainer Leeb

IPC: G10L15/22 ,  G10L15/02 ,  G10L15/18

CPC classification number: G10L15/22 ,  G06F17/2785 ,  G10L15/1815 ,  G10L2015/221

Abstract: Systems perform methods of interpreting spoken utterances from a user and responding to the utterances by providing requested information or performing a requested action. The utterances are interpreted in the context of multiple domains. Each interpretation is assigned a relevancy score based on how well the interpretation represents what the speaker intended. Interpretations having a relevancy score below a threshold for its associated domain are discarded. A remaining interpretation is chosen based on choosing the most relevant domain for the utterance. The user may be prompted to provide disambiguation information that can be used to choose the best domain. Storing past associations of utterance representation and domain choice allows for measuring the strength of correlation between uttered words and phrases with relevant domains. This correlation strength information may allow the system to automatically disambiguate alternate interpretations without requiring user input.

公开(公告)号：US10229683B2

公开(公告)日：2019-03-12

申请号：US15456354

申请日：2017-03-10

Applicant: SoundHound, Inc.

Inventor： Rainer Leeb

IPC: G10L15/22 ,  G10L15/02 ,  G10L15/18

Abstract: Systems perform methods of interpreting spoken utterances from a user and responding to the utterances by providing requested information or performing a requested action. The utterances are interpreted in the context of multiple domains. Each interpretation is assigned a relevancy score based on how well the interpretation represents what the speaker intended. Interpretations having a relevancy score below a threshold for its associated domain are discarded. A remaining interpretation is chosen based on choosing the most relevant domain for the utterance. The user may be prompted to provide disambiguation information that can be used to choose the best domain. Storing past associations of utterance representation and domain choice allows for measuring the strength of correlation between uttered words and phrases with relevant domains. This correlation strength information may allow the system to automatically disambiguate alternate interpretations without requiring user input.

公开(公告)号：US20180315415A1

公开(公告)日：2018-11-01

申请号：US15497208

申请日：2017-04-26

Applicant: SoundHound, Inc.

Inventor： Glenda Mosley ,  Rainer Leeb ,  Stephanie Lawson ,  Kamyar Mohajer

IPC: G10L15/01 ,  G10L15/06

Abstract: Virtual assistants provide results in response to user commands and analyze user utterances in response to the result. The analysis can interpret words, recognized from the utterance, as being negative indicators that imply user dissatisfaction. Virtual assistants request follow-up information from users. Analysis also interprets words as indicators of clarification and collect information to add to a knowledgebase. Machine learning algorithms use recognized words to train a behavioral model to improve results. Virtual assistants also infer, from replacement of words in successive commands, that earlier commands had word recognition errors and infer, from addition of words, that earlier commands had interpretation errors. Virtual assistants act locally or as devices in communication with servers.