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公开(公告)号：US20240187522A1
公开(公告)日：2024-06-06
申请号：US18074674
申请日：2022-12-05
IPC分类号： H04M3/51
CPC分类号： H04M3/5133 , H04M3/5166
摘要： Apparatus and methods for a chatbot deflection program are provided. A chatbot may receive an input it is unable to answer or parse. The chatbot may transfer the chat to an agent for a response. The chatbot may provide a search field for the agent. The agent may review the input and query the chatbot. The chatbot may provide an answer. The agent may provide a response to the input, using the answer. The response may be transmitted to the user. The chat may be transferred back to the chatbot.
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公开(公告)号：US11798551B2
公开(公告)日：2023-10-24
申请号：US17212076
申请日：2021-03-25
发明人： Ashwini Patil , Ramakrishna R. Yannam , Ion Gerald McCusker , Saahithi Chillara , Ravisha Andar , Emad Noorizadeh , Priyank R. Shah , Yogesh Raghuvanshi , Sushil Golani , Christopher Keith Restorff
IPC分类号： G10L15/00 , G10L13/027 , G10L15/22 , G06N20/00 , G06N7/01
CPC分类号： G10L15/22 , G06N7/01 , G06N20/00 , G10L2015/225
摘要： An apparatus includes a memory and a processor. The memory stores first and second machine learning algorithms. The processor receives, from a user, voice signals associated with an information request and converts them into text. The processor uses the first machine learning algorithm to determine, based on the text, to automatically generate a reply to the request, rather than transmitting the request to an agent. This determination indicates that the text is associated with a probability that the automatically generated reply includes the requested information that is greater than a threshold. The processor uses the second machine learning algorithm to generate, based on the set of text, the reply, which it transmits to the user. The processor receives feedback associated with the reply, indicating that the reply does or does not include the requested information. The processor uses the feedback to update either or both machine learning algorithms.
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公开(公告)号：US11782974B2
公开(公告)日：2023-10-10
申请号：US17212014
申请日：2021-03-25
发明人： Ashwini Patil , Ramakrishna R. Yannam , Ion Gerald McCusker , Saahithi Chillara , Ravisha Andar , Emad Noorizadeh , Pravin Kumar Sankari Bhagavathiappan , Yogesh Raghuvanshi , Sushil Golani
摘要： An apparatus includes a memory and processor. The memory stores previous requests and corresponding previous responses. The processor determines that a user device transmitted a new voice request, converts the voice request into a first set of text, and transmits the text to an agent device. The processor applies the machine learning algorithm to the first set of text to generate suggested responses, by identifying patterns shared by the first set of text and a subset of the previous requests that are associated with the suggested responses. The processor transmits the suggested responses to the agent device. The processor then determines that the agent device transmitted voice signals responding to the new request. The processor converts these voice signals into a second set of text. The processor stores the first set of text as a previous request, and the second set of text as a corresponding previous response.
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公开(公告)号：US20220147522A1
公开(公告)日：2022-05-12
申请号：US17094342
申请日：2020-11-10
IPC分类号： G06F16/242 , G06N20/00 , G06F8/61 , H04L29/06 , G06F40/274 , G06F40/117
摘要： Systems, computer program products, and methods are described herein for generating customized data input options using machine learning techniques. The present invention is configured to electronically receive, from a computing device of a user, an input query; retrieve, from a database associated with an entity, information associated with the user; determine a resource distribution profile of the user, wherein the resource distribution profile comprises one or more resource transfers executed by the user; generate one or more customized autocomplete options for the input query based on at least the information associated with the user and the resource distribution profile of the user; and transmit control signals configured to cause the computing device of the user to display the one or more customized autocomplete options to the user.
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5.发明授权公开(公告)号：US11115530B1
公开(公告)日：2021-09-07
申请号：US16908893
申请日：2020-06-23
摘要： When a caller initiates a conversation with an interactive voice response (“IVR”) system, the caller may be transferred to a live agent. Apparatus and methods are provided for integrating automated tools and artificial intelligence (“AI”) into the interaction with the IVR system. The automated tools and AI may track the conversation to decipher when to transfer the caller to the agent. The agent may determine which machine generated responses are appropriate for the caller. AI may be leveraged to suggest responses for both caller and agent while they are interacting with each other. The agent may transfer back the caller to the IVR system along with the appropriate machine generated response to maintain efficiency and shorten time of human agent interaction.
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公开(公告)号：US11966821B2
公开(公告)日：2024-04-23
申请号：US16997134
申请日：2020-08-19
发明人： Ion Gerald McCusker , Ramakrishna R. Yannam , Ravisha Andar , Bharathiraja Krishnamoorthy , Emad Noorizadeh
CPC分类号： G06N20/00 , G06T1/20 , G10L15/063
摘要： A system for reducing computational load for training machine learning models is provided. The system may provide an end-to-end-solution for automating development, testing and updating of machine learning models in various operational environments. The system may determine which machine learning models included in a computer program product need to be retrained in response to a change in training data. For a computer program product that includes multiple models, the system only retrains target models, resulting in significant savings in computing resources. The system may also reduce the number of machine learning models that need to be generated for testing environments, further reducing consumption of computational resources.
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公开(公告)号：US11551674B2
公开(公告)日：2023-01-10
申请号：US16996106
申请日：2020-08-18
发明人： Prejish Thomas , Ravisha Andar , Saahithi Chillara , Emad Noorizadeh , Priyank R. Shah , Ramakrishna R. Yannam
摘要： Aspects of the disclosure relate to systems and methods for increasing the speed, accuracy, and efficiency of language processing systems. A provided method may include storing a plurality of distinct rule sets in a database. Each of the rule sets may be associated with a different pipeline from a set of pipelines. The method may include receiving the utterance. The method may include tokenizing and/or annotating the utterance, determining a pipeline for the utterance, and comparing the utterance to the rule set that is associated with the pipeline. When a match is achieved between the utterance and the rule set, the method may include resolving the intent of the utterance based on the match. The method may include transmitting a request corresponding to the intent to a central server, receiving a response, and transmitting the response to the system user.
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公开(公告)号：US20220303390A1
公开(公告)日：2022-09-22
申请号：US17203059
申请日：2021-03-16
发明人： Ramakrishna R. Yannam , Donatus Asumu , Ion Gerald McCusker , Saahithi Chillara , Ashwini Patil , Ravisha Andar , Emad Noorizadeh , Priyank R. Shah , Devanshu Mukherjee
摘要： A device that is configured to assign users to an issue cluster based on issue types for the users. The device is further configured to identify available agents and to assign each available agent to one or more knowledge area clusters based on knowledge scores. A knowledge score indicates an expertise level for an agent in a knowledge area. The device is further configured to identify an issue cluster that is associated with an issue type and to identify a user from the issue cluster. The device is further configured to identify a knowledge area cluster that is associated with the issue type and to identify an agent from the knowledge area cluster. The device is further configured to establish a network connection between a user device associated with the user and a user device associated with the agent.
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公开(公告)号：US20220300885A1
公开(公告)日：2022-09-22
申请号：US17202979
申请日：2021-03-16
发明人： Ramakrishna R. Yannam , Donatus Asumu , Ion Gerald McCusker , Saahithi Chillara , Ashwini Patil , Ravisha Andar , Emad Noorizadeh , Priyank R. Shah
摘要： A device that is configured to establish a network connection between a user and an agent. The device is further configured to identify a first issue type for the user and to identify a first resolution type provided by the agent based on a conversation between the user and the agent. The device is further configured to identify a performance score from a resolution mapping based on a combination of the first issue type and the first resolution type. The device is further configured to identify a first knowledge area that is associated with the first issue type and to update a first knowledge score that is associated with the first knowledge area in a performance record for the agent based on the performance score. The device is further configured to send a recommendation to the agent based at least in part on the performance score.
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公开(公告)号：US11379759B2
公开(公告)日：2022-07-05
申请号：US17471316
申请日：2021-09-10
IPC分类号： H04L12/18 , G06N20/00 , H04L51/046 , H04L65/1069 , H04L51/04 , H04L51/216 , H04L41/50
摘要： Methods for leveraging a plurality of machine-learning algorithms to improve a chat interaction are provided. The methods may include monitoring for initiation of a live chat session; alerting and assigning a chat responder to the live chat session; engaging one or more of a plurality of automated chat tools, the tools loaded with artificial intelligence (AI), in order to improve the response of the responder during the session; reviewing and retrieving, using the AI, from a machine learning (ML) library in electronic communication with the AI, historical information; presenting, on a chat responder screen, selected actionable information generated based on the historical information, to the responder; integrating, based on pre-determined conditions, chat responses into the ML library; and integrating into the ML library, based on the same or other pre-determined conditions, chat comments. The chat comments are generated by a chat initiator.
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