Patents by Inventor Lambert Mathias
Lambert Mathias 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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Publication number: 20220148590Abstract: Features are disclosed for processing a user utterance with respect to multiple subject matters or domains, and for selecting a likely result from a particular domain with which to respond to the utterance or otherwise take action. A user utterance may be transcribed by an automatic speech recognition (“ASR”) module, and the results may be provided to a multi-domain natural language understanding (“NLU”) engine. The multi-domain NLU engine may process the transcription(s) in multiple individual domains rather than in a single domain. In some cases, the transcription(s) may be processed in multiple individual domains in parallel or substantially simultaneously. In addition, hints may be generated based on previous user interactions and other data. The ASR module, multi-domain NLU engine, and other components of a spoken language processing system may use the hints to more efficiently process input or more accurately generate output.Type: ApplicationFiled: November 12, 2021Publication date: May 12, 2022Inventors: Lambert Mathias, Ying Shi, Imre Attila Kiss, Ryan Paul Thomas, Frederic Johan Georges Deramat
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Patent number: 11189277Abstract: In speech processing systems personalization is added in the Natural Language Understanding (NLU) processor by incorporating external knowledge sources of user information to improve entity recognition performance of the speech processing system. Personalization in the NLU is effected by incorporating one or more dictionaries of entries, or gazetteers, with information personal to a respective user, that provide the user's information to permit disambiguation of semantic interpretation for input utterances to improve quality of speech processing results.Type: GrantFiled: February 13, 2019Date of Patent: November 30, 2021Assignee: Amazon Technologies, Inc.Inventors: Imre Attila Kiss, Arthur Richard Toth, Lambert Mathias
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Patent number: 11176936Abstract: Features are disclosed for processing a user utterance with respect to multiple subject matters or domains, and for selecting a likely result from a particular domain with which to respond to the utterance or otherwise take action. A user utterance may be transcribed by an automatic speech recognition (“ASR”) module, and the results may be provided to a multi-domain natural language understanding (“NLU”) engine. The multi-domain NLU engine may process the transcription(s) in multiple individual domains rather than in a single domain. In some cases, the transcription(s) may be processed in multiple individual domains in parallel or substantially simultaneously. In addition, hints may be generated based on previous user interactions and other data. The ASR module, multi-domain NLU engine, and other components of a spoken language processing system may use the hints to more efficiently process input or more accurately generate output.Type: GrantFiled: May 1, 2019Date of Patent: November 16, 2021Assignee: Amazon Technologies, Inc.Inventors: Lambert Mathias, Ying Shi, Imre Attila Kiss, Ryan Paul Thomas, Frederic Johan Georges Deramat
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Patent number: 10726831Abstract: Features are disclosed for processing and interpreting natural language, such as interpretations of user utterances, in multi-turn dialog interactions. Context information regarding interpretations of user utterances and system responses to the user utterances can be maintained. Subsequent user utterances can be interpreted using the context information, rather than being interpreted without context. In some cases, interpretations of subsequent user utterances can be merged with interpretations of prior user utterances using a rule-based framework. Rules may be defined to determine which interpretations may be merged and under what circumstances they may be merged.Type: GrantFiled: May 20, 2014Date of Patent: July 28, 2020Assignee: Amazon Technologies, Inc.Inventors: Giuseppe Di Fabbrizio, Shishir Sridhar Bharathi, Ying Shi, Lambert Mathias
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Publication number: 20190325873Abstract: Features are disclosed for processing a user utterance with respect to multiple subject matters or domains, and for selecting a likely result from a particular domain with which to respond to the utterance or otherwise take action. A user utterance may be transcribed by an automatic speech recognition (“ASR”) module, and the results may be provided to a multi-domain natural language understanding (“NLU”) engine. The multi-domain NLU engine may process the transcription(s) in multiple individual domains rather than in a single domain. In some cases, the transcription(s) may be processed in multiple individual domains in parallel or substantially simultaneously. In addition, hints may be generated based on previous user interactions and other data. The ASR module, multi-domain NLU engine, and other components of a spoken language processing system may use the hints to more efficiently process input or more accurately generate output.Type: ApplicationFiled: May 1, 2019Publication date: October 24, 2019Inventors: Lambert Mathias, Ying Shi, Imre Attila Kiss, Ryan Paul Thomas, Frederic Johan Georges Deramat
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Publication number: 20190318737Abstract: In speech processing systems personalization is added in the Natural Language Understanding (NLU) processor by incorporating external knowledge sources of user information to improve entity recognition performance of the speech processing system. Personalization in the NLU is effected by incorporating one or more dictionaries of entries, or gazetteers, with information personal to a respective user, that provide the user's information to permit disambiguation of semantic interpretation for input utterances to improve quality of speech processing results.Type: ApplicationFiled: February 13, 2019Publication date: October 17, 2019Inventors: Imre Attila Kiss, Arthur Richard Toth, Lambert Mathias
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Patent number: 10304444Abstract: A system capable of performing natural language understanding (NLU) without the concept of a domain that influences NLU results. The present system uses a hierarchical organizations of intents/commands and entity types, and trained models associated with those hierarchies, so that commands and entity types may be determined for incoming text queries without necessarily determining a domain for the incoming text. The system thus operates in a domain agnostic manner, in a departure from multi-domain architecture NLU processing where a system determines NLU results for multiple domains simultaneously and then ranks them to determine which to select as the result.Type: GrantFiled: June 29, 2016Date of Patent: May 28, 2019Assignee: Amazon Technologies, Inc.Inventors: Lambert Mathias, Thomas Kollar, Arindam Mandal, Angeliki Metallinou
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Patent number: 10283119Abstract: Features are disclosed for processing a user utterance with respect to multiple subject matters or domains, and for selecting a likely result from a particular domain with which to respond to the utterance or otherwise take action. A user utterance may be transcribed by an automatic speech recognition (“ASR”) module, and the results may be provided to a multi-domain natural language understanding (“NLU”) engine. The multi-domain NLU engine may process the transcription(s) in multiple individual domains rather than in a single domain. In some cases, the transcription(s) may be processed in multiple individual domains in parallel or substantially simultaneously. In addition, hints may be generated based on previous user interactions and other data. The ASR module, multi-domain NLU engine, and other components of a spoken language processing system may use the hints to more efficiently process input or more accurately generate output.Type: GrantFiled: April 30, 2018Date of Patent: May 7, 2019Assignee: Amazon Technologies, Inc.Inventors: Lambert Mathias, Ying Shi, Imre Attila Kiss, Ryan Paul Thomas, Frederic Johan Georges Deramat
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Patent number: 10224030Abstract: In speech processing systems personalization is added in the Natural Language Understanding (NLU) processor by incorporating external knowledge sources of user information to improve entity recognition performance of the speech processing system. Personalization in the NLU is effected by incorporating one or more dictionaries of entries, or gazetteers, with information personal to a respective user, that provide the user's information to permit disambiguation of semantic interpretation for input utterances to improve quality of speech processing results.Type: GrantFiled: March 14, 2013Date of Patent: March 5, 2019Assignee: AMAZON TECHNOLOGIES, INC.Inventors: Imre Attila Kiss, Arthur Richard Toth, Lambert Mathias
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Patent number: 10210862Abstract: Neural networks may be used in certain automatic speech recognition systems. To improve performance at these neural networks, the present system converts the lattice into a matrix form, thus maintaining certain information included in the lattice that might otherwise be lost while also placing the lattice in a form that may be manipulated by other components to perform operations such as checking ASR results. The matrix representation of the lattice may be transformed into a vector representation by calculations performed at a recurrent neural network (RNN). By representing the lattice as a vector representation the system may perform additional operations, such as ASR results confirmation.Type: GrantFiled: April 6, 2016Date of Patent: February 19, 2019Assignee: Amazon Technologies, Inc.Inventors: Faisal Ladhak, Ankur Gandhe, Markus Dreyer, Ariya Rastrow, Björn Hoffmeister, Lambert Mathias
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Patent number: 10176802Abstract: An automatic speech recognition (ASR) system may convert an ASR output lattice into a matrix form, thus maintaining certain information included in the lattice that might otherwise be lost in an N-best list output. The matrix representation of the lattice may be encoded using a recurrent neural network (RNN) to create a vector representation of the lattice. The vector representation may then be used by the system to perform additional operations, such as ASR results confirmation.Type: GrantFiled: April 6, 2016Date of Patent: January 8, 2019Assignee: Amazon Technologies, Inc.Inventors: Faisal Ladhak, Ankur Gandhe, Markus Dreyer, Ariya Rastrow, Björn Hoffmeister, Lambert Mathias
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Publication number: 20180315425Abstract: Features are disclosed for processing a user utterance with respect to multiple subject matters or domains, and for selecting a likely result from a particular domain with which to respond to the utterance or otherwise take action. A user utterance may be transcribed by an automatic speech recognition (“ASR”) module, and the results may be provided to a multi-domain natural language understanding (“NLU”) engine. The multi-domain NLU engine may process the transcription(s) in multiple individual domains rather than in a single domain. In some cases, the transcription(s) may be processed in multiple individual domains in parallel or substantially simultaneously. In addition, hints may be generated based on previous user interactions and other data. The ASR module, multi-domain NLU engine, and other components of a spoken language processing system may use the hints to more efficiently process input or more accurately generate output.Type: ApplicationFiled: April 30, 2018Publication date: November 1, 2018Inventors: Lambert Mathias, Ying Shi, Imre Attila Kiss, Ryan Paul Thomas, Frederic Johan Georges Deramat
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Patent number: 9959869Abstract: Features are disclosed for processing a user utterance with respect to multiple subject matters or domains, and for selecting a likely result from a particular domain with which to respond to the utterance or otherwise take action. A user utterance may be transcribed by an automatic speech recognition (“ASR”) module, and the results may be provided to a multi-domain natural language understanding (“NLU”) engine. The multi-domain NLU engine may process the transcription(s) in multiple individual domains rather than in a single domain. In some cases, the transcription(s) may be processed in multiple individual domains in parallel or substantially simultaneously. In addition, hints may be generated based on previous user interactions and other data. The ASR module, multi-domain NLU engine, and other components of a spoken language processing system may use the hints to more efficiently process input or more accurately generate output.Type: GrantFiled: September 4, 2017Date of Patent: May 1, 2018Assignee: Amazon Technologies, Inc.Inventors: Lambert Mathias, Ying Shi, Imre Attila Kiss, Ryan Paul Thomas, Frederic Johan Georges Deramat
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Publication number: 20180012597Abstract: Features are disclosed for processing a user utterance with respect to multiple subject matters or domains, and for selecting a likely result from a particular domain with which to respond to the utterance or otherwise take action. A user utterance may be transcribed by an automatic speech recognition (“ASR”) module, and the results may be provided to a multi-domain natural language understanding (“NLU”) engine. The multi-domain NLU engine may process the transcription(s) in multiple individual domains rather than in a single domain. In some cases, the transcription(s) may be processed in multiple individual domains in parallel or substantially simultaneously. In addition, hints may be generated based on previous user interactions and other data. The ASR module, multi-domain NLU engine, and other components of a spoken language processing system may use the hints to more efficiently process input or more accurately generate output.Type: ApplicationFiled: September 4, 2017Publication date: January 11, 2018Inventors: Lambert Mathias., Ying Shi., Imre Attila Kiss., Ryan Paul Thomas., Frederic Johan Georges Deramat.
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Publication number: 20170278514Abstract: A system capable of performing natural language understanding (NLU) without the concept of a domain that influences NLU results. The present system uses a hierarchical organizations of intents/commands and entity types, and trained models associated with those hierarchies, so that commands and entity types may be determined for incoming text queries without necessarily determining a domain for the incoming text. The system thus operates in a domain agnostic manner, in a departure from multi-domain architecture NLU processing where a system determines NLU results for multiple domains simultaneously and then ranks them to determine which to select as the result.Type: ApplicationFiled: June 29, 2016Publication date: September 28, 2017Inventors: Lambert Mathias, Thomas Kollar, Arindam Mandal, Angeliki Metallinou
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Patent number: 9754589Abstract: Features are disclosed for processing a user utterance with respect to multiple subject matters or domains, and for selecting a likely result from a particular domain with which to respond to the utterance or otherwise take action. A user utterance may be transcribed by an automatic speech recognition (“ASR”) module, and the results may be provided to a multi-domain natural language understanding (“NLU”) engine. The multi-domain NLU engine may process the transcription(s) in multiple individual domains rather than in a single domain. In some cases, the transcription(s) may be processed in multiple individual domains in parallel or substantially simultaneously. In addition, hints may be generated based on previous user interactions and other data. The ASR module, multi-domain NLU engine, and other components of a spoken language processing system may use the hints to more efficiently process input or more accurately generate output.Type: GrantFiled: September 2, 2016Date of Patent: September 5, 2017Assignee: Amazon Technologies, Inc.Inventors: Lambert Mathias, Ying Shi, Imre Attila Kiss, Ryan Paul Thomas, Frederic Johan Georges Deramat
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Patent number: 9691379Abstract: A speech-based system may be configured to receive and act upon spoken requests from a user. In some cases, a spoken request may ask the system to play content such as music without specifying from which of multiple available content sources the music is to be obtained. In response to such a request, the system analyzes feature scores for each of the content sources. The feature scores indicate usage characteristics of the different sources by a current user or groups of users. The features scores for a particular source may be averaged or otherwise combined to create a composite score, and the source having the highest composite score is selected as the source of the requested content.Type: GrantFiled: June 26, 2014Date of Patent: June 27, 2017Assignee: Amazon Technologies, Inc.Inventors: Lambert Mathias, Stephen Frederick Potter
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Publication number: 20170116985Abstract: Features are disclosed for processing a user utterance with respect to multiple subject matters or domains, and for selecting a likely result from a particular domain with which to respond to the utterance or otherwise take action. A user utterance may be transcribed by an automatic speech recognition (“ASR”) module, and the results may be provided to a multi-domain natural language understanding (“NLU”) engine. The multi-domain NLU engine may process the transcription(s) in multiple individual domains rather than in a single domain. In some cases, the transcription(s) may be processed in multiple individual domains in parallel or substantially simultaneously. In addition, hints may be generated based on previous user interactions and other data. The ASR module, multi-domain NLU engine, and other components of a spoken language processing system may use the hints to more efficiently process input or more accurately generate output.Type: ApplicationFiled: September 2, 2016Publication date: April 27, 2017Inventors: Lambert Mathias, Ying Shi, Imre Attila Kiss, Ryan Paul Thomas, Frederic Johan Georges Deramat
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Patent number: 9520124Abstract: A system is provided for training an acoustic model for use in speech recognition. In particular, such a system may be used to perform training based on a spoken audio stream and a non-literal transcript of the spoken audio stream. Such a system may identify text in the non-literal transcript which represents concepts having multiple spoken forms. The system may attempt to identify the actual spoken form in the audio stream which produced the corresponding text in the non-literal transcript, and thereby produce a revised transcript which more accurately represents the spoken audio stream. The revised, and more accurate, transcript may be used to train the acoustic model using discriminative training techniques, thereby producing a better acoustic model than that which would be produced using conventional techniques, which perform training based directly on the original non-literal transcript.Type: GrantFiled: November 16, 2015Date of Patent: December 13, 2016Assignee: MModal IP LLCInventors: Lambert Mathias, Girija Yegnanarayanan, Juergen Fritsch
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Patent number: 9478216Abstract: A method for speech recognition is implemented in the specific form of computer processes that function in a computer processor. That is, one or more computer processes: process a speech input to produce a sequence of representative speech vectors and perform multiple recognition passes to determine a recognition output corresponding to the speech input. At least one generic recognition pass is based on a generic speech recognition arrangement using generic modeling of a broad general class of input speech. And at least one adapted recognition pass is based on a speech adapted arrangement using pre-adapted modeling of a specific sub-class of the general class of input speech.Type: GrantFiled: December 8, 2009Date of Patent: October 25, 2016Assignee: Nuance Communications, Inc.Inventors: Daniel Willett, Lambert Mathias, Chuang He, Jianxiong Wu