Patents by Inventor Ziad Al Bawab
Ziad Al Bawab 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: 11676576Abstract: Systems and methods are provided for acquiring training data and building an organizational-based language model based on the training data. In organizational data is generated via one or more applications associated with an organization, the collected organizational data is aggregated and filtered into training data that is used for training an organizational-based language model for speech processing based on the training data.Type: GrantFiled: August 11, 2021Date of Patent: June 13, 2023Assignee: Microsoft Technology Licensing, LLCInventors: Ziad Al Bawab, Anand U Desai, Cem Aksoylar, Michael Levit, Xin Meng, Shuangyu Chang, Suyash Choudhury, Dhiresh Rawal, Tao Li, Rishi Girish, Marcus Jager, Ananth Rampura Sheshagiri Rao
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Patent number: 11636854Abstract: A system includes acquisition of meeting data associated with a meeting, determination of a plurality of meeting participants based on the acquired meeting data, acquisition of e-mail data associated with each of the plurality of meeting participants, generation of a meeting language model based on the acquired e-mail data and the meeting data, and transcription of audio associated with the meeting based on the meeting language model.Type: GrantFiled: May 24, 2022Date of Patent: April 25, 2023Assignee: Microsoft Technology Licensing, LLCInventors: Ziad Al Bawab, Anand U Desai, Shuangyu Chang, Amit K Agarwal, Zoltan Romocsa, Christopher H Basoglu, Nathan E Wohlgemuth
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Patent number: 11562738Abstract: A system includes acquisition of a domain grammar, determination of an interpolated grammar based on the domain grammar and a base grammar, determination of a delta domain grammar based on an augmented first grammar and the interpolated grammar, determination of an out-of-vocabulary class based on the domain grammar and the base grammar, insertion of the out-of-vocabulary class into a composed transducer composed of the augmented first grammar and one or more other transducers to generate an updated composed transducer, composition of the delta domain grammar and the updated composed transducer, and application of the composition of the delta domain grammar and the updated composed transducer to an output of an acoustic model.Type: GrantFiled: October 28, 2019Date of Patent: January 24, 2023Assignee: MICROSOFT TECHNOLOGY LICENSING, LLCInventors: Ziad Al Bawab, Anand U Desai, Shuangyu Chang, Amit K Agarwal, Zoltan Romocsa, Veljko Miljanic, Aadyot Bhatnagar, Hosam Khalil, Christopher Basoglu
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Publication number: 20220358912Abstract: A system includes acquisition of meeting data associated with a meeting, determination of a plurality of meeting participants based on the acquired meeting data, acquisition of e-mail data associated with each of the plurality of meeting participants, generation of a meeting language model based on the acquired e-mail data and the meeting data, and transcription of audio associated with the meeting based on the meeting language model.Type: ApplicationFiled: May 24, 2022Publication date: November 10, 2022Inventors: Ziad AL BAWAB, Anand U. DESAI, Shuangyu CHANG, Amit K. AGARWAL, Zoltan ROMOCSA, Christopher H. BASOGLU, Nathan E. WOHLGEMUTH
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Patent number: 11430433Abstract: A system includes acquisition of meeting data associated with a meeting, determination of a plurality of meeting participants based on the acquired meeting data, acquisition of e-mail data associated with each of the plurality of meeting participants, generation of a meeting language model based on the acquired e-mail data and the meeting data, and transcription of audio associated with the meeting based on the meeting language model.Type: GrantFiled: August 5, 2019Date of Patent: August 30, 2022Assignee: MICROSOFT TECHNOLOGY LICENSING, LLCInventors: Ziad Al Bawab, Anand U Desai, Shuangyu Chang, Amit K Agarwal, Zoltan Romocsa, Christopher H Basoglu, Nathan E Wohlgemuth
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Patent number: 11348574Abstract: A system includes acquisition of meeting data associated with a meeting, determination of a plurality of meeting participants based on the acquired meeting data, acquisition of e-mail data associated with each of the plurality of meeting participants, generation of a meeting language model based on the acquired e-mail data and the meeting data, and transcription of audio associated with the meeting based on the meeting language model.Type: GrantFiled: August 5, 2019Date of Patent: May 31, 2022Assignee: MICROSOFT TECHNOLOGY LICENSING, LLCInventors: Ziad Al Bawab, Anand U Desai, Shuangyu Chang, Amit K Agarwal, Zoltan Romocsa, Christopher H Basoglu, Nathan E Wohlgemuth
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Publication number: 20220013109Abstract: Provided is a system and method for acquiring training data and building an organizational-based language model based on the training data. In one example, the method may include collecting organizational data that is generated via one or more applications associated with an organization, aggregating the collected organizational data with previously collected organizational data to generate aggregated organizational training data, training an organizational-based language model for speech processing based on the aggregated organizational training data, and storing the trained organizational-based language model.Type: ApplicationFiled: August 11, 2021Publication date: January 13, 2022Inventors: Ziad AL BAWAB, Anand U. DESAI, Cem AKSOYLAR, Michael LEVIT, Xin MENG, Shuangyu CHANG, Suyash CHOUDHURY, Dhiresh RAWAL, Tao LI, Rishi GIRISH, Marcus JAGER, Ananth Rampura SHESHAGIRI RAO
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Patent number: 11120788Abstract: Provided is a system and method for acquiring training data and building an organizational-based language model based on the training data. In one example, the method may include collecting organizational data that is generated via one or more applications associated with an organization, aggregating the collected organizational data with previously collected organizational data to generate aggregated organizational training data, training an organizational-based language model for speech processing based on the aggregated organizational training data, and storing the trained organizational-based language model.Type: GrantFiled: June 27, 2019Date of Patent: September 14, 2021Assignee: MICROSOFT TECHNOLOGY LICENSING, LLCInventors: Ziad Al Bawab, Anand U Desai, Cem Aksoylar, Michael Levit, Xin Meng, Shuangyu Chang, Suyash Choudhury, Dhiresh Rawal, Tao Li, Rishi Girish, Marcus Jager, Ananth Rampura Sheshagiri Rao
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Patent number: 10847147Abstract: Automatic speech recognition systems can benefit from cues in user voice such as hyperarticulation. Traditional approaches typically attempt to define and detect an absolute state of hyperarticulation, which is very difficult, especially on short voice queries. This disclosure provides for an approach for hyperarticulation detection using pair-wise comparisons and on a real-world speech recognition system. The disclosed approach uses delta features extracted from a pair of repetitive user utterances. The improvements provided by the disclosed systems and methods include improvements in word error rate by using hyperarticulation information as a feature in a second pass N-best hypotheses rescoring setup.Type: GrantFiled: May 24, 2019Date of Patent: November 24, 2020Assignee: Microsoft Technology Licensing, LLCInventors: Ranjitha Gurunath Kulkarni, Ahmed Moustafa El Kholy, Ziad Al Bawab, Noha Alon, Imed Zitouni
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Publication number: 20200349930Abstract: A system includes acquisition of a domain grammar, determination of an interpolated grammar based on the domain grammar and a base grammar, determination of a delta domain grammar based on an augmented first grammar and the interpolated grammar, determination of an out-of-vocabulary class based on the domain grammar and the base grammar, insertion of the out-of-vocabulary class into a composed transducer composed of the augmented first grammar and one or more other transducers to generate an updated composed transducer, composition of the delta domain grammar and the updated composed transducer, and application of the composition of the delta domain grammar and the updated composed transducer to an output of an acoustic model.Type: ApplicationFiled: October 28, 2019Publication date: November 5, 2020Inventors: Ziad AL BAWAB, Anand U. DESAI, Shuangyu CHANG, Amit K. AGARWAL, Zoltan ROMOCSA, Veljko MILJANIC, Aadyot BHATNAGAR, Hosam KHALIL, Christopher BASOGLU
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Publication number: 20200349931Abstract: A system includes acquisition of meeting data associated with a meeting, determination of a plurality of meeting participants based on the acquired meeting data, acquisition of e-mail data associated with each of the plurality of meeting participants, generation of a meeting language model based on the acquired e-mail data and the meeting data, and transcription of audio associated with the meeting based on the meeting language model.Type: ApplicationFiled: August 5, 2019Publication date: November 5, 2020Inventors: Ziad AL BAWAB, Anand U. DESAI, Shuangyu CHANG, Amit K. AGARWAL, Zoltan ROMOCSA, Christopher H. BASOGLU, Nathan E. WOHLGEMUTH
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Publication number: 20200349920Abstract: Provided is a system and method for acquiring training data and building an organizational-based language model based on the training data. In one example, the method may include collecting organizational data that is generated via one or more applications associated with an organization, aggregating the collected organizational data with previously collected organizational data to generate aggregated organizational training data, training an organizational-based language model for speech processing based on the aggregated organizational training data, and storing the trained organizational-based language model.Type: ApplicationFiled: June 27, 2019Publication date: November 5, 2020Inventors: Ziad AL BAWAB, Anand U DESAI, Cem AKSOYLAR, Michael LEVIT, Xin MENG, Shuangyu CHANG, Suyash CHOUDHURY, Dhiresh RAWAL, Tao LI, Rishi GIRISH, Marcus JAGER, Ananth Rampura SHESHAGIRI RAO
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Patent number: 10706852Abstract: The described technology provides arbitration between speech recognition results generated by different automatic speech recognition (ASR) engines, such as ASR engines trained according to different language or acoustic models. The system includes an arbitrator that selects between a first speech recognition result representing an acoustic utterance as transcribed by a first ASR engine and a second speech recognition result representing the acoustic utterance as transcribed by a second ASR engine. This selection is based on a set of confidence features that is initially used by the first ASR engine or the second ASR engine to generate the first and second speech recognition results.Type: GrantFiled: November 13, 2015Date of Patent: July 7, 2020Assignee: Microsoft Technology Licensing, LLCInventors: Kshitiz Kumar, Hosam Khalil, Yifan Gong, Ziad Al-Bawab, Chaojun Liu
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Publication number: 20190279612Abstract: Automatic speech recognition systems can benefit from cues in user voice such as hyperarticulation. Traditional approaches typically attempt to define and detect an absolute state of hyperarticulation, which is very difficult, especially on short voice queries. This disclosure provides for an approach for hyperarticulation detection using pair-wise comparisons and on a real-world speech recognition system. The disclosed approach uses delta features extracted from a pair of repetitive user utterances. The improvements provided by the disclosed systems and methods include improvements in word error rate by using hyperarticulation information as a feature in a second pass N-best hypotheses rescoring setup.Type: ApplicationFiled: May 24, 2019Publication date: September 12, 2019Inventors: Ranjitha Gurunath Kulkarni, Ahmed Moustafa El Kholy, Ziad Al Bawab, Noha Alon, Imed Zitouni
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Patent number: 10354642Abstract: Automatic speech recognition systems can benefit from cues in user voice such as hyperarticulation. Traditional approaches typically attempt to define and detect an absolute state of hyperarticulation, which is very difficult, especially on short voice queries. This disclosure provides for an approach for hyperarticulation detection using pair-wise comparisons and on a real-world speech recognition system. The disclosed approach uses delta features extracted from a pair of repetitive user utterances. The improvements provided by the disclosed systems and methods include improvements in word error rate by using hyperarticulation information as a feature in a second pass N-best hypotheses rescoring setup.Type: GrantFiled: June 15, 2017Date of Patent: July 16, 2019Assignee: Microsoft Technology Licensing, LLCInventors: Ranjitha Gurunath Kulkarni, Ahmed Moustafa El Kholy, Ziad Al Bawab, Noha Alon, Imed Zitouni
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Publication number: 20180254035Abstract: Automatic speech recognition systems can benefit from cues in user voice such as hyperarticulation. Traditional approaches typically attempt to define and detect an absolute state of hyperarticulation, which is very difficult, especially on short voice queries. This disclosure provides for an approach for hyperarticulation detection using pair-wise comparisons and on a real-world speech recognition system. The disclosed approach uses delta features extracted from a pair of repetitive user utterances. The improvements provided by the disclosed systems and methods include improvements in word error rate by using hyperarticulation information as a feature in a second pass N-best hypotheses rescoring setup.Type: ApplicationFiled: June 15, 2017Publication date: September 6, 2018Inventors: Ranjitha Gurunath Kulkarni, Ahmed Moustafa El Kholy, Ziad Al Bawab, Noha Alon, Imed Zitouni
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Patent number: 9947317Abstract: A new pronunciation learning system for dynamically learning new pronunciations assisted by user correction logs. The user correction logs provide a record of speech recognition events and subsequent user behavior that implicitly confirms or rejects the recognition result and/or shows the user's intended words by via subsequent input. The system analyzes the correction logs and distills them down to a set of words which lack acceptable pronunciations. Hypothetical pronunciations, constrained by spelling and other linguistic knowledge, are generated for each of the words. Offline recognition determines the hypothetical pronunciations with a good acoustical match to the audio data likely to contain the words. The matching pronunciations are aggregated and adjudicated to select new pronunciations for the words to improve general or personalized recognition models.Type: GrantFiled: February 13, 2017Date of Patent: April 17, 2018Assignee: Microsoft Technology Licensing, LLCInventors: Nicholas Kibre, Umut Ozertem, Sarangarajan Parthasarathy, Ziad Al Bawab
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Publication number: 20170154623Abstract: A new pronunciation learning system for dynamically learning new pronunciations assisted by user correction logs. The user correction logs provide a record of speech recognition events and subsequent user behavior that implicitly confirms or rejects the recognition result and/or shows the user's intended words by via subsequent input. The system analyzes the correction logs and distills them down to a set of words which lack acceptable pronunciations. Hypothetical pronunciations, constrained by spelling and other linguistic knowledge, are generated for each of the words. Offline recognition determines the hypothetical pronunciations with a good acoustical match to the audio data likely to contain the words. The matching pronunciations are aggregated and adjudicated to select new pronunciations for the words to improve general or personalized recognition models.Type: ApplicationFiled: February 13, 2017Publication date: June 1, 2017Applicant: Microsoft Technology Licensing, LLC.Inventors: Nicholas Kibre, Umut Ozertem, Sarangarajan Parthasarathy, Ziad Al Bawab
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Publication number: 20170140759Abstract: The described technology provides arbitration between speech recognition results generated by different automatic speech recognition (ASR) engines, such as ASR engines trained according to different language or acoustic models. The system includes an arbitrator that selects between a first speech recognition result representing an acoustic utterance as transcribed by a first ASR engine and a second speech recognition result representing the acoustic utterance as transcribed by a second ASR engine. This selection is based on a set of confidence features that is initially used by the first ASR engine or the second ASR engine to generate the first and second speech recognition results.Type: ApplicationFiled: November 13, 2015Publication date: May 18, 2017Inventors: Kshitiz Kumar, Hosam Khalil, Yifan Gong, Ziad Al-Bawab, Chaojun Liu
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Patent number: 9589562Abstract: A new pronunciation learning system for dynamically learning new pronunciations assisted by user correction logs. The user correction logs provide a record of speech recognition events and subsequent user behavior that implicitly confirms or rejects the recognition result and/or shows the user's intended words by via subsequent input. The system analyzes the correction logs and distills them down to a set of words which lack acceptable pronunciations. Hypothetical pronunciations, constrained by spelling and other linguistic knowledge, are generated for each of the words. Offline recognition determines the hypothetical pronunciations with a good acoustical match to the audio data likely to contain the words. The matching pronunciations are aggregated and adjudicated to select new pronunciations for the words to improve general or personalized recognition models.Type: GrantFiled: February 21, 2014Date of Patent: March 7, 2017Assignee: Microsoft Technology Licensing, LLCInventors: Nicholas Kibre, Umut Ozertem, Sarangarajan Parthasarathy, Ziad Al Bawab