Patents by Inventor Tomer Amiaz
Tomer Amiaz has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11990133Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for an automated calling system are disclosed. In one aspect, a method includes the actions of receiving audio data of an utterance spoken by a user who is having a telephone conversation with a bot. The actions further include determining a context of the telephone conversation. The actions further include determining a user intent of a first previous portion of the telephone conversation spoken by the user and a bot intent of a second previous portion of the telephone conversation outputted by a speech synthesizer of the bot. The actions further include, based on the audio data of the utterance, the context of the telephone conversation, the user intent, and the bot intent, generating synthesized speech of a reply by the bot to the utterance. The actions further include, providing, for output, the synthesized speech.Type: GrantFiled: July 7, 2023Date of Patent: May 21, 2024Assignee: GOOGLE LLCInventors: Asaf Aharoni, Arun Narayanan, Nir Shabat, Parisa Haghani, Galen Tsai Chuang, Yaniv Leviathan, Neeraj Gaur, Pedro J. Moreno Mengibar, Rohit Prakash Prabhavalkar, Zhongdi Qu, Austin Severn Waters, Tomer Amiaz, Michiel A. U. Bacchiani
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Publication number: 20240146668Abstract: Implementations are directed to updating a trained voice bot that is deployed for conducting conversations on behalf of a third-party. A third-party developer can interact with a voice bot development system that enables the third-party developer to train, update, validate, and monitor performance of the trained voice bot. In various implementations, the trained voice bot can be updated by updating a corpus of training instances that was initially utilized to train the voice bot, and updating the trained voice bot based on the updated corpus. In some implementations, the corpus of training instances may be updated in response to identifying occurrence(s) of behavioral error(s) of the trained voice bot while the conversations are being conducted on behalf of the third-party. In additional or alternative implementations, the corpus of training instances may be updated in response to determining the trained voice bot does not include a desired behavior.Type: ApplicationFiled: January 3, 2024Publication date: May 2, 2024Inventors: Asaf Aharoni, Eyal Segalis, Ofer Ron, Sasha Goldshtein, Tomer Amiaz, Razvan Mathias, Yaniv Leviathan
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Patent number: 11902222Abstract: Implementations are directed to updating a trained voice bot that is deployed for conducting conversations on behalf of a third-party. A third-party developer can interact with a voice bot development system that enables the third-party developer to train, update, validate, and monitor performance of the trained voice bot. In various implementations, the trained voice bot can be updated by updating a corpus of training instances that was initially utilized to train the voice bot, and updating the trained voice bot based on the updated corpus. In some implementations, the corpus of training instances may be updated in response to identifying occurrence(s) of behavioral error(s) of the trained voice bot while the conversations are being conducted on behalf of the third-party. In additional or alternative implementations, the corpus of training instances may be updated in response to determining the trained voice bot does not include a desired behavior.Type: GrantFiled: February 8, 2021Date of Patent: February 13, 2024Assignee: GOOGLE LLCInventors: Asaf Aharoni, Eyal Segalis, Ofer Ron, Sasha Goldshtein, Tomer Amiaz, Razvan Mathias, Yaniv Leviathan
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Publication number: 20230419964Abstract: Implementations are directed to causing a voice bot to utilize a plurality of ML layers in resolving unique personal identifier(s) for a human while the voice bot is engaged in a corresponding conversation with the human. The unique personal identifier(s) can include a unique sequence of alphanumeric characters that is personal to the human. In some implementations, ASR speech hypothes(es) corresponding to spoken utterance(s) that include the unique personal identifier(s) can be processed to generate candidate unique personal identifier(s), given alphanumeric character(s) of the candidate unique personal identifier(s) can be selected, and the voice bot can prompt the human with clarification request(s) to clarify the given alphanumeric character(s) until it is predicted to correspond to the an actual unique personal identifier(s) for the human(s). The unique personal identifier(s) can then be utilized in performance of further action(s) by the voice bot and/or other systems.Type: ApplicationFiled: September 7, 2023Publication date: December 28, 2023Inventors: Rafael Goldfarb, Or Guz, Lior Alon, Assaf Hurwitz Michaely, Golan Pundak, Shmuel Leibtag, Tomer Amiaz, Dan Rasin, Asaf Aharoni
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Publication number: 20230352027Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for an automated calling system are disclosed. In one aspect, a method includes the actions of receiving audio data of an utterance spoken by a user who is having a telephone conversation with a bot. The actions further include determining a context of the telephone conversation. The actions further include determining a user intent of a first previous portion of the telephone conversation spoken by the user and a bot intent of a second previous portion of the telephone conversation outputted by a speech synthesizer of the bot. The actions further include, based on the audio data of the utterance, the context of the telephone conversation, the user intent, and the bot intent, generating synthesized speech of a reply by the bot to the utterance. The actions further include, providing, for output, the synthesized speech.Type: ApplicationFiled: July 7, 2023Publication date: November 2, 2023Inventors: Asaf Aharoni, Arun Narayanan, Nir Shabat, Parisa Haghani, Galen Tsai Chuang, Yaniv Leviathan, Neeraj Gaur, Pedro J. Moreno Mengibar, Rohit Prakash Prabhavalkar, Zhongdi Qu, Austin Severn Waters, Tomer Amiaz, Michiel A.U. Bacchiani
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Patent number: 11804211Abstract: Implementations are directed to providing a voice bot development platform that enables a third-party developer to train a voice bot based on training instance(s). The training instance(s) can each include training input and training output. The training input can include a portion of a corresponding conversation and a prior context of the corresponding conversation. The training output can include a corresponding ground truth response to the portion of the corresponding conversation. Subsequent to training, the voice bot can be deployed for conducting conversations on behalf of a third-party. In some implementations, the voice bot is further trained based on a corresponding feature emphasis input that attentions the voice bot to a particular feature of the portion of the corresponding conversation. In some additional or alternative implementations, the voice bot is further trained to interact with third-party system(s) via remote procedure calls (RPCs).Type: GrantFiled: December 4, 2020Date of Patent: October 31, 2023Assignee: GOOGLE LLCInventors: Asaf Aharoni, Yaniv Leviathan, Eyal Segalis, Gal Elidan, Sasha Goldshtein, Tomer Amiaz, Deborah Cohen
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Patent number: 11790906Abstract: Implementations are directed to causing a voice bot to utilize a plurality of ML layers in resolving unique personal identifier(s) for a human while the voice bot is engaged in a corresponding conversation with the human. The unique personal identifier(s) can include a unique sequence of alphanumeric characters that is personal to the human. In some implementations, ASR speech hypothes(es) corresponding to spoken utterance(s) that include the unique personal identifier(s) can be processed to generate candidate unique personal identifier(s), given alphanumeric character(s) of the candidate unique personal identifier(s) can be selected, and the voice bot can prompt the human with clarification request(s) to clarify the given alphanumeric character(s) until it is predicted to correspond to the an actual unique personal identifier(s) for the human(s). The unique personal identifier(s) can then be utilized in performance of further action(s) by the voice bot and/or other systems.Type: GrantFiled: January 25, 2021Date of Patent: October 17, 2023Assignee: GOOGLE LLCInventors: Rafael Goldfarb, Or Guz, Lior Alon, Assaf Hurwitz Michaely, Golan Pundak, Shmuel Leibtag, Tomer Amiaz, Dan Rasin, Asaf Aharoni
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Patent number: 11741966Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for an automated calling system are disclosed. In one aspect, a method includes the actions of receiving audio data of an utterance spoken by a user who is having a telephone conversation with a bot. The actions further include determining a context of the telephone conversation. The actions further include determining a user intent of a first previous portion of the telephone conversation spoken by the user and a bot intent of a second previous portion of the telephone conversation outputted by a speech synthesizer of the bot. The actions further include, based on the audio data of the utterance, the context of the telephone conversation, the user intent, and the bot intent, generating synthesized speech of a reply by the bot to the utterance. The actions further include, providing, for output, the synthesized speech.Type: GrantFiled: October 12, 2022Date of Patent: August 29, 2023Assignee: GOOGLE LLCInventors: Asaf Aharoni, Arun Narayanan, Nir Shabat, Parisa Haghani, Galen Tsai Chuang, Yaniv Leviathan, Neeraj Gaur, Pedro J. Moreno Mengibar, Rohit Prakash Prabhavalkar, Zhongdi Qu, Austin Severn Waters, Tomer Amiaz, Michiel A. U. Bacchiani
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Patent number: 11727939Abstract: A network node in a communication network receives, from a user equipment, a cluster of audio segments. The network node calculates a first confidence measure representing a first probability that a first speaker model represents a speaker of the cluster of audio segments. The network node also calculates a second confidence measure representing a second probability that a second speaker model represents the speaker of the cluster of audio segments. In response to the first confidence measure and the second confidence measure both representing probabilities that are higher than a target probability, the network node updates a first user profile associated with the first speaker model and a second user profile associated with the second speaker model based on a user preference assigned to the cluster of audio segments.Type: GrantFiled: January 5, 2022Date of Patent: August 15, 2023Assignee: TELEFONAKTIEBOLAGET LM ERICSSON (PUBL)Inventors: Volodya Grancharov, Tomer Amiaz, Hadar Gecht, Harald Pobloth
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Publication number: 20230038343Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for an automated calling system are disclosed. In one aspect, a method includes the actions of receiving audio data of an utterance spoken by a user who is having a telephone conversation with a bot. The actions further include determining a context of the telephone conversation. The actions further include determining a user intent of a first previous portion of the telephone conversation spoken by the user and a bot intent of a second previous portion of the telephone conversation outputted by a speech synthesizer of the bot. The actions further include, based on the audio data of the utterance, the context of the telephone conversation, the user intent, and the bot intent, generating synthesized speech of a reply by the bot to the utterance. The actions further include, providing, for output, the synthesized speech.Type: ApplicationFiled: October 12, 2022Publication date: February 9, 2023Inventors: Asaf Aharoni, Arun Narayanan, Nir Shabat, Parisa Haghani, Galen Tsai Chuang, Yaniv Leviathan, Neeraj Gaur, Pedro J. Moreno Mengibar, Rohit Prakash Prabhavalkar, Zhongdi Qu, Austin Severn Waters, Tomer Amiaz, Michiel A.U. Bacchiani
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Patent number: 11495233Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for an automated calling system are disclosed. In one aspect, a method includes the actions of receiving audio data of an utterance spoken by a user who is having a telephone conversation with a bot. The actions further include determining a context of the telephone conversation. The actions further include determining a user intent of a first previous portion of the telephone conversation spoken by the user and a bot intent of a second previous portion of the telephone conversation outputted by a speech synthesizer of the bot. The actions further include, based on the audio data of the utterance, the context of the telephone conversation, the user intent, and the bot intent, generating synthesized speech of a reply by the bot to the utterance. The actions further include, providing, for output, the synthesized speech.Type: GrantFiled: October 20, 2021Date of Patent: November 8, 2022Assignee: GOOGLE LLCInventors: Asaf Aharoni, Arun Narayanan, Nir Shabat, Parisa Haghani, Galen Tsai Chuang, Yaniv Leviathan, Neeraj Gaur, Pedro J. Moreno Mengibar, Rohit Prakash Prabhavalkar, Zhongdi Qu, Austin Severn Waters, Tomer Amiaz, Michiel A.U. Bacchiani
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Patent number: 11430449Abstract: A management of user profiles comprises calculating, for an audio segment, a user confidence measure representing a probability that the audio segment comprises speech of a user and a group confidence measure representing a probability that the audio segment comprises speech of a group of users. A user profile is then managed based on a comparison between the user confidence measure and a user confidence threshold and between the group confidence measure and a group confidence threshold. The embodiments thereby achieve an efficient voice-controlled user profile management by utilizing a layered approach that provides user profiles for group of users as fallback when the identity of the speaking user can not accurately be recognized.Type: GrantFiled: September 11, 2017Date of Patent: August 30, 2022Assignee: Telefonaktiebolaget LM Ericsson (publ)Inventors: Volodya Grancharov, Tomer Amiaz, Hadar Gecht, Harald Pobloth
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Publication number: 20220255885Abstract: Implementations are directed to updating a trained voice bot that is deployed for conducting conversations on behalf of a third-party. A third-party developer can interact with a voice bot development system that enables the third-party developer to train, update, validate, and monitor performance of the trained voice bot. In various implementations, the trained voice bot can be updated by updating a corpus of training instances that was initially utilized to train the voice bot, and updating the trained voice bot based on the updated corpus. In some implementations, the corpus of training instances may be updated in response to identifying occurrence(s) of behavioral error(s) of the trained voice bot while the conversations are being conducted on behalf of the third-party. In additional or alternative implementations, the corpus of training instances may be updated in response to determining the trained voice bot does not include a desired behavior.Type: ApplicationFiled: February 8, 2021Publication date: August 11, 2022Inventors: Asaf Aharoni, Eyal Segalis, Ofer Ron, Sasha Goldshtein, Tomer Amiaz, Razvan Mathias, Yaniv Leviathan
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Publication number: 20220238105Abstract: Implementations are directed to causing a voice bot to utilize a plurality of ML layers in resolving unique personal identifier(s) for a human while the voice bot is engaged in a corresponding conversation with the human. The unique personal identifier(s) can include a unique sequence of alphanumeric characters that is personal to the human. In some implementations, ASR speech hypothes(es) corresponding to spoken utterance(s) that include the unique personal identifier(s) can be processed to generate candidate unique personal identifier(s), given alphanumeric character(s) of the candidate unique personal identifier(s) can be selected, and the voice bot can prompt the human with clarification request(s) to clarify the given alphanumeric character(s) until it is predicted to correspond to the an actual unique personal identifier(s) for the human(s). The unique personal identifier(s) can then be utilized in performance of further action(s) by the voice bot and/or other systems.Type: ApplicationFiled: January 25, 2021Publication date: July 28, 2022Inventors: Rafael Goldfarb, Or Guz, Lior Alon, Assaf Hurwitz Michaely, Golan Pundak, Shmuel Leibtag, Tomer Amiaz, Dan Rasin, Asaf Aharoni
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Publication number: 20220180858Abstract: Implementations are directed to providing a voice bot development platform that enables a third-party developer to train a voice bot based on training instance(s). The training instance(s) can each include training input and training output. The training input can include a portion of a corresponding conversation and a prior context of the corresponding conversation. The training output can include a corresponding ground truth response to the portion of the corresponding conversation. Subsequent to training, the voice bot can be deployed for conducting conversations on behalf of a third-party. In some implementations, the voice bot is further trained based on a corresponding feature emphasis input that attentions the voice bot to a particular feature of the portion of the corresponding conversation. In some additional or alternative implementations, the voice bot is further trained to interact with third-party system(s) via remote procedure calls (RPCs).Type: ApplicationFiled: December 2, 2021Publication date: June 9, 2022Inventors: Asaf Aharoni, Yaniv LEVIATHAN, Eyal SEGALIS, Gal ELIDAN, Sasha Goldshtein, Tomer Amiaz, Deborah Cohen
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Publication number: 20220180857Abstract: Implementations are directed to providing a voice bot development platform that enables a third-party developer to train a voice bot based on training instance(s). The training instance(s) can each include training input and training output. The training input can include a portion of a corresponding conversation and a prior context of the corresponding conversation. The training output can include a corresponding ground truth response to the portion of the corresponding conversation. Subsequent to training, the voice bot can be deployed for conducting conversations on behalf of a third-party. In some implementations, the voice bot is further trained based on a corresponding feature emphasis input that attentions the voice bot to a particular feature of the portion of the corresponding conversation. In some additional or alternative implementations, the voice bot is further trained to interact with third-party system(s) via remote procedure calls (RPCs).Type: ApplicationFiled: December 4, 2020Publication date: June 9, 2022Inventors: Asaf Aharoni, Yaniv LEVIATHAN, Eyal SEGALIS, Gal ELIDAN, Sasha Goldshtein, Tomer Amiaz, Deborah Cohen
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Publication number: 20220130395Abstract: A network node in a communication network receives, from a user equipment, a cluster of audio segments. The network node calculates a first confidence measure representing a first probability that a first speaker model represents a speaker of the cluster of audio segments. The network node also calculates a second confidence measure representing a second probability that a second speaker model represents the speaker of the cluster of audio segments. In response to the first confidence measure and the second confidence measure both representing probabilities that are higher than a target probability, the network node updates a first user profile associated with the first speaker model and a second user profile associated with the second speaker model based on a user preference assigned to the cluster of audio segments.Type: ApplicationFiled: January 5, 2022Publication date: April 28, 2022Inventors: Volodya Grancharov, Tomer Amiaz, Hadar Gecht, Harald Pobloth
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Publication number: 20220044684Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for an automated calling system are disclosed. In one aspect, a method includes the actions of receiving audio data of an utterance spoken by a user who is having a telephone conversation with a bot. The actions further include determining a context of the telephone conversation. The actions further include determining a user intent of a first previous portion of the telephone conversation spoken by the user and a bot intent of a second previous portion of the telephone conversation outputted by a speech synthesizer of the bot. The actions further include, based on the audio data of the utterance, the context of the telephone conversation, the user intent, and the bot intent, generating synthesized speech of a reply by the bot to the utterance. The actions further include, providing, for output, the synthesized speech.Type: ApplicationFiled: October 20, 2021Publication date: February 10, 2022Inventors: Asaf Aharoni, Arun Narayanan, Nir Shabat, Parisa Haghani, Galen Tsai Chuang, Yaniv LEVIATHAN, Neeraj Gaur, Pedro J. Moreno Mengibar, Rohit Prakash Prabhavalkar, Zhongdi Qu, Austin Severn Waters, Tomer Amiaz, Michiel A.U. Bacchiani
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Patent number: 11227605Abstract: A management of user profiles comprises calculating, for each speaker model of at least one speaker model, a confidence measure representing a probability that the speaker model represents a speaker of a cluster of audio segments. A user profile associated with the speaker model is updated based on a user preference assigned to the cluster of audio segments if the confidence measure calculated for the speaker model represents a probability that is higher than a target probability. The embodiments achieve an efficient user profile management in a voice-controlled context but without the need for any dedicated enrollment sessions to train speaker models.Type: GrantFiled: September 11, 2017Date of Patent: January 18, 2022Assignee: TELEFONAKTIEBOLAGET LM ERICSSON (PUBL)Inventors: Volodya Grancharov, Tomer Amiaz, Hadar Gecht, Harald Pobloth
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Patent number: 11158321Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for an automated calling system are disclosed. In one aspect, a method includes the actions of receiving audio data of an utterance spoken by a user who is having a telephone conversation with a bot. The actions further include determining a context of the telephone conversation. The actions further include determining a user intent of a first previous portion of the telephone conversation spoken by the user and a bot intent of a second previous portion of the telephone conversation outputted by a speech synthesizer of the bot. The actions further include, based on the audio data of the utterance, the context of the telephone conversation, the user intent, and the bot intent, generating synthesized speech of a reply by the bot to the utterance. The actions further include, providing, for output, the synthesized speech.Type: GrantFiled: September 24, 2019Date of Patent: October 26, 2021Assignee: GOOGLE LLCInventors: Asaf Aharoni, Arun Narayanan, Nir Shabat, Parisa Haghani, Galen Tsai Chuang, Yaniv Leviathan, Neeraj Gaur, Pedro J. Moreno Mengibar, Rohit Prakash Prabhavalkar, Zhongdi Qu, Austin Severn Waters, Tomer Amiaz, Michiel A. U. Bacchiani