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1.发明授权公开(公告)号：US11606463B1
公开(公告)日：2023-03-14
申请号：US16836487
申请日：2020-03-31
Applicant: Interactions LLC
Inventor： Yoryos Yeracaris , Michael Johnston , Ethan Selfridge , Phillip Gray , Patrick Haffner
Abstract: A virtual assistant system for communicating with customers uses human intelligence to correct any errors in the system AI, while collecting data for machine learning and future improvements for more automation. The system may use a modular design, with separate components for carrying out different system functions and sub-functions, and with frameworks for selecting the component best able to respond to a given customer conversation.
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公开(公告)号：US20190035389A1
公开(公告)日：2019-01-31
申请号：US16148884
申请日：2018-10-01
Applicant: Interactions LLC
Inventor： Ethan Selfridge , Michael Johnston
IPC: G10L15/197 , G10L15/06 , G10L15/02
CPC classification number: G10L15/197 , G10L15/02 , G10L15/063 , G10L2015/0631
Abstract: A speech interpretation module interprets the audio of user utterances as sequences of words. To do so, the speech interpretation module parameterizes a literal corpus of expressions by identifying portions of the expressions that correspond to known concepts, and generates a parameterized statistical model from the resulting parameterized corpus. When speech is received the speech interpretation module uses a hierarchical speech recognition decoder that uses both the parameterized statistical model and language sub-models that specify how to recognize a sequence of words. The separation of the language sub-models from the statistical model beneficially reduces the size of the literal corpus needed for training, reduces the size of the resulting model, provides more fine-grained interpretation of concepts, and improves computational efficiency by allowing run-time incorporation of the language sub-models.
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公开(公告)号：US10096317B2
公开(公告)日：2018-10-09
申请号：US15131833
申请日：2016-04-18
Applicant: Interactions LLC
Inventor： Ethan Selfridge , Michael Johnston
IPC: G10L15/02 , G10L15/197 , G10L15/06
Abstract: A speech interpretation module interprets the audio of user utterances as sequences of words. To do so, the speech interpretation module parameterizes a literal corpus of expressions by identifying portions of the expressions that correspond to known concepts, and generates a parameterized statistical model from the resulting parameterized corpus. When speech is received the speech interpretation module uses a hierarchical speech recognition decoder that uses both the parameterized statistical model and language sub-models that specify how to recognize a sequence of words. The separation of the language sub-models from the statistical model beneficially reduces the size of the literal corpus needed for training, reduces the size of the resulting model, provides more fine-grained interpretation of concepts, and improves computational efficiency by allowing run-time incorporation of the language sub-models.
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4.发明授权公开(公告)号：US12003668B1
公开(公告)日：2024-06-04
申请号：US17346071
申请日：2021-06-11
Applicant: Interactions LLC
Inventor： Yoryos Yeracaris , Michael Johnston , Ethan Selfridge , Phillip Gray , Patrick Haffner
CPC classification number: H04M3/4938 , G10L13/00 , G10L15/01 , G10L21/10 , H04M3/4933 , H04M3/4936 , H04M3/5232 , H04M3/5237 , H04M3/5315 , H04M3/5322 , H04M2203/355
Abstract: A virtual assistant system for communicating with customers uses human intelligence to correct any errors in the system AI, while collecting data for machine learning and future improvements for more automation. The system may use a modular design, with separate components for carrying out different system functions and sub-functions, and with frameworks for selecting the component best able to respond to a given customer conversation.
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Patent Agency Ranking
公开(公告)号：US10482876B2
公开(公告)日：2019-11-19
申请号：US16148884
申请日：2018-10-01
Applicant: Interactions LLC
Inventor： Ethan Selfridge , Michael Johnston
IPC: G06F17/27 , G10L15/197 , G10L15/02 , G10L15/06
Abstract: A speech interpretation module interprets the audio of user utterances as sequences of words. To do so, the speech interpretation module parameterizes a literal corpus of expressions by identifying portions of the expressions that correspond to known concepts, and generates a parameterized statistical model from the resulting parameterized corpus. When speech is received the speech interpretation module uses a hierarchical speech recognition decoder that uses both the parameterized statistical model and language sub-models that specify how to recognize a sequence of words. The separation of the language sub-models from the statistical model beneficially reduces the size of the literal corpus needed for training, reduces the size of the resulting model, provides more fine-grained interpretation of concepts, and improves computational efficiency by allowing run-time incorporation of the language sub-models.
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公开(公告)号：US20170301346A1
公开(公告)日：2017-10-19
申请号：US15131833
申请日：2016-04-18
Applicant: Interactions LLC
Inventor： Ethan Selfridge , Michael Johnston
IPC: G10L15/197 , G10L15/02 , G10L15/06
CPC classification number: G10L15/197 , G10L15/02 , G10L15/063 , G10L2015/0631
Abstract: A speech interpretation module interprets the audio of user utterances as sequences of words. To do so, the speech interpretation module parameterizes a literal corpus of expressions by identifying portions of the expressions that correspond to known concepts, and generates a parameterized statistical model from the resulting parameterized corpus. When speech is received the speech interpretation module uses a hierarchical speech recognition decoder that uses both the parameterized statistical model and language sub-models that specify how to recognize a sequence of words. The separation of the language sub-models from the statistical model beneficially reduces the size of the literal corpus needed for training, reduces the size of the resulting model, provides more fine-grained interpretation of concepts, and improves computational efficiency by allowing run-time incorporation of the language sub-models.
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公开(公告)号：US11210461B2
公开(公告)日：2021-12-28
申请号：US16027202
申请日：2018-07-03
Applicant: Interactions LLC
Inventor： David Thomson , Ethan Selfridge
IPC: G06F40/205 , G10L25/51 , G10L15/22 , G10L15/06 , G10L15/18 , H04M3/42 , H04L29/06 , G06F40/20 , H04M3/51
Abstract: A masking system prevents a human agent from receiving sensitive personal information (SPI) provided by a caller during caller-agent communication. The masking system includes components for detecting the SPI, including automated speech recognition and natural language processing systems. When the caller communicates with the agent, e.g., via a phone call, the masking system processes the incoming caller audio. When the masking system detects SPI in the caller audio stream or when the masking system determines a high likelihood that incoming caller audio will include SPI, the caller audio is masked such that it cannot be heard by the agent. The masking system collects the SPI from the caller audio and sends it to the organization associated with the agent for processing the caller's request or transaction without giving the agent access to caller SPI.
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公开(公告)号：US11314942B1
公开(公告)日：2022-04-26
申请号：US16825856
申请日：2020-03-20
Applicant: Interactions LLC
Inventor： Ethan Selfridge , Michael Johnston , Robert Lifgren , James Dreher , John Leonard
Abstract: A computer-implemented method for providing agent assisted transcriptions of user utterances. A user utterance is received in response to a prompt provided to the user at a remote client device. An automatic transcription is generated from the utterance using a language model based upon an application or context, and presented to a human agent. The agent reviews the transcription and may replace at least a portion of the transcription with a corrected transcription. As the agent inputs the corrected transcription, accelerants are presented to the user comprising suggested texted to be inputted. The accelerants may be determined based upon an agent input, an application or context of the transcription, the portion of the transcription being replaced, or any combination thereof. In some cases, the user provides textual input, to which the agent transcribes an intent associated with the input with the aid of one or more accelerants.
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公开(公告)号：US20190013038A1
公开(公告)日：2019-01-10
申请号：US16027202
申请日：2018-07-03
Applicant: Interactions LLC
Inventor： David Thomson , Ethan Selfridge
Abstract: A masking system prevents a human agent from receiving sensitive personal information (SPI) provided by a caller during caller-agent communication. The masking system includes components for detecting the SPI, including automated speech recognition and natural language processing systems. When the caller communicates with the agent, e.g., via a phone call, the masking system processes the incoming caller audio. When the masking system detects SPI in the caller audio stream or when the masking system determines a high likelihood that incoming caller audio will include SPI, the caller audio is masked such that it cannot be heard by the agent. The masking system collects the SPI from the caller audio and sends it to the organization associated with the agent for processing the caller's request or transaction without giving the agent access to caller SPI.
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