Patents by Inventor John Hershey
John Hershey 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: 11086918Abstract: A method for performing multi-label classification includes extracting a feature vector from an input vector including input data by a feature extractor, determining, by a label predictor, a relevant vector including relevant labels having relevant scores based on the feature vector, updating a binary masking vector by masking pre-selected labels having been selected in previous label selections, applying the updated binary masking vector to the relevant vector such that the relevant label vector is updated to exclude the pre-selected labels from the relevant labels, and selecting a relevant label from the updated relevant label vector based on the relevant scores of the updated relevant label vector.Type: GrantFiled: December 7, 2016Date of Patent: August 10, 2021Assignee: Mitsubishi Electric Research Laboratories, Inc.Inventors: Takaaki Hori, Chiori Hori, Shinji Watanabe, John Hershey, Bret Harsham, Jonathan Le Roux
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Patent number: 10811000Abstract: Systems and methods for a speech recognition system for recognizing speech including overlapping speech by multiple speakers. The system including a hardware processor. A computer storage memory to store data along with having computer-executable instructions stored thereon that, when executed by the processor is to implement a stored speech recognition network. An input interface to receive an acoustic signal, the received acoustic signal including a mixture of speech signals by multiple speakers, wherein the multiple speakers include target speakers. An encoder network and a decoder network of the stored speech recognition network are trained to transform the received acoustic signal into a text for each target speaker. Such that the encoder network outputs a set of recognition encodings, and the decoder network uses the set of recognition encodings to output the text for each target speaker. An output interface to transmit the text for each target speaker.Type: GrantFiled: April 13, 2018Date of Patent: October 20, 2020Assignee: Mitsubishi Electric Research Laboratories, Inc.Inventors: Jonathan Le Roux, Takaaki Hori, Shane Settle, Hiroshi Seki, Shinji Watanabe, John Hershey
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Patent number: 10726856Abstract: Systems and methods for audio signal processing including an input interface to receive a noisy audio signal including a mixture of target audio signal and noise. An encoder to map each time-frequency bin of the noisy audio signal to one or more phase-related value from one or more phase quantization codebook of phase-related values indicative of the phase of the target signal. Calculate, for each time-frequency bin of the noisy audio signal, a magnitude ratio value indicative of a ratio of a magnitude of the target audio signal to a magnitude of the noisy audio signal. A filter to cancel the noise from the noisy audio signal based on the phase-related values and the magnitude ratio values to produce an enhanced audio signal. An output interface to output the enhanced audio signal.Type: GrantFiled: August 16, 2018Date of Patent: July 28, 2020Assignee: Mitsubishi Electric Research Laboratories, Inc.Inventors: Jonathan Le Roux, Shinji Watanabe, John Hershey, Gordon Wichern
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Patent number: 10672388Abstract: A speech recognition system includes an input device to receive voice sounds, one or more processors, and one or more storage devices storing parameters and program modules including instructions which cause the one or more processors to perform operations.Type: GrantFiled: December 15, 2017Date of Patent: June 2, 2020Assignee: Mitsubishi Electric Research Laboratories, Inc.Inventors: Takaaki Hori, Shinji Watanabe, John Hershey
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Patent number: 10592800Abstract: A method for transforms input signals, by first defining a model for transforming the input signals, wherein the model is specified by constraints and a set of model parameters. An iterative inference procedure is derived from the model and the set of model parameters and unfolded into a set of layers, wherein there is one layer for each iteration of the procedure, and wherein a same set of network parameters is used by all layers. A neural network is formed by untying the set of network parameters such that there is one set of network parameters for each layer and each set of network parameters is separately maintainable and separately applicable to the corresponding layer. The neural network is trained to obtain a trained neural network, and then input signals are transformed using the trained neural network to obtain output signals.Type: GrantFiled: November 3, 2016Date of Patent: March 17, 2020Assignee: Mitsubishi Electric Research Laboratories, Inc.Inventors: John Hershey, Jonathan Le Roux, Felix Weninger
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Patent number: 10593321Abstract: A method for training a multi-language speech recognition network includes providing utterance datasets corresponding to predetermined languages, inserting language identification (ID) labels into the utterance datasets, wherein each of the utterance datasets is labelled by each of the language ID labels, concatenating the labeled utterance datasets, generating initial network parameters from the utterance datasets, selecting the initial network parameters according to a predetermined sequence, and training, iteratively, an end-to-end network with a series of the selected initial network parameters and the concatenated labeled utterance datasets until a training result reaches a threshold.Type: GrantFiled: December 15, 2017Date of Patent: March 17, 2020Assignee: Mitsubishi Electric Research Laboratories, Inc.Inventors: Shinji Watanabe, Takaaki Hori, Hiroshi Seki, Jonathan Le Roux, John Hershey
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Publication number: 20200058314Abstract: Systems and methods for audio signal processing including an input interface to receive a noisy audio signal including a mixture of target audio signal and noise. An encoder to map each time-frequency bin of the noisy audio signal to one or more phase-related value from one or more phase quantization codebook of phase-related values indicative of the phase of the target signal. Calculate, for each time-frequency bin of the noisy audio signal, a magnitude ratio value indicative of a ratio of a magnitude of the target audio signal to a magnitude of the noisy audio signal. A filter to cancel the noise from the noisy audio signal based on the phase-related values and the magnitude ratio values to produce an enhanced audio signal. An output interface to output the enhanced audio signal.Type: ApplicationFiled: August 16, 2018Publication date: February 20, 2020Inventors: Jonathan Le Roux, Shinji Watanabe, John Hershey, Gordon Wichem
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Publication number: 20190318725Abstract: Systems and methods for a speech recognition system for recognizing speech including overlapping speech by multiple speakers. The system including a hardware processor. A computer storage memory to store data along with having computer-executable instructions stored thereon that, when executed by the processor is to implement a stored speech recognition network. An input interface to receive an acoustic signal, the received acoustic signal including a mixture of speech signals by multiple speakers, wherein the multiple speakers include target speakers. An encoder network and a decoder network of the stored speech recognition network are trained to transform the received acoustic signal into a text for each target speaker. Such that the encoder network outputs a set of recognition encodings, and the decoder network uses the set of recognition encodings to output the text for each target speaker. An output interface to transmit the text for each target speaker.Type: ApplicationFiled: April 13, 2018Publication date: October 17, 2019Inventors: Jonathan Le Roux, Takaaki Hori, Shane Settle, Hiroshi Seki, Shinji Watanabe, John Hershey
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Patent number: 10417498Abstract: A system for generating a word sequence includes one or more processors in connection with a memory and one or more storage devices storing instructions causing operations that include receiving first and second input vectors, extracting first and second feature vectors, estimating a first set of weights and a second set of weights, calculating a first content vector from the first set of weights and the first feature vectors, and calculating a second content vector, transforming the first content vector into a first modal content vector having a predetermined dimension and transforming the second content vector into a second modal content vector having the predetermined dimension, estimating a set of modal attention weights, generating a weighted content vector having the predetermined dimension from the set of modal attention weights and the first and second modal content vectors, and generating a predicted word using the sequence generator.Type: GrantFiled: March 29, 2017Date of Patent: September 17, 2019Assignee: Mitsubishi Electric Research Laboratories, Inc.Inventors: Chiori Hori, Takaaki Hori, John Hershey, Tim Marks
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Publication number: 20190189111Abstract: A method for training a multi-language speech recognition network includes providing utterance datasets corresponding to predetermined languages, inserting language identification (ID) labels into the utterance datasets, wherein each of the utterance datasets is labelled by each of the language ID labels, concatenating the labeled utterance datasets, generating initial network parameters from the utterance datasets, selecting the initial network parameters according to a predetermined sequence, and training, iteratively, an end-to-end network with a series of the selected initial network parameters and the concatenated labeled utterance datasets until a training result reaches a threshold.Type: ApplicationFiled: December 15, 2017Publication date: June 20, 2019Inventors: Shinji Watanabe, Takaaki Hori, Hiroshi Seki, Jonathan Le Roux, John Hershey
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Publication number: 20190189115Abstract: A speech recognition system includes an input device to receive voice sounds, one or more processors, and one or more storage devices storing parameters and program modules including instructions which cause the one or more processors to perform operations.Type: ApplicationFiled: December 15, 2017Publication date: June 20, 2019Inventors: Takaaki Hori, Shinji Watanabe, John Hershey
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Patent number: 10176799Abstract: A method and for training a language model to reduce recognition errors, wherein the language model is a recurrent neural network language model (RNNLM) by first acquiring training samples. An automatic speech recognition system (ASR) is applied to the training samples to produce recognized words and probabilites of the recognized words, and an N-best list is selected from the recognized words based on the probabilities. determining word errors using reference data for hypotheses in the N-best list. The hypotheses are rescored using the RNNLM. Then, we determine gradients for the hypotheses using the word errors and gradients for words in the hypotheses. Lastly, parameters of the RNNLM are updated using a sum of the gradients.Type: GrantFiled: February 2, 2016Date of Patent: January 8, 2019Assignee: Mitsubishi Electric Research Laboratories, Inc.Inventors: Takaaki Hori, Chiori Hori, Shinji Watanabe, John Hershey
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Patent number: 10150556Abstract: A airborne vehicle comprising a fuselage, a folding wing-like structure which is movable from a stowed position to a deployed position, and a hinge mechanism which couples the folding wing-like structure to the fuselage in a manner so that the folding wing-like structure displaces and rotates during movement from the stowed position to the deployed position. The hinge mechanism is housed within an outer mold line of the fuselage and folding wing-like structure to decrease the signature of the airborne vehicle.Type: GrantFiled: May 23, 2016Date of Patent: December 11, 2018Assignee: The Boeing CompanyInventors: Daniel Christopher Stanley, John Hershey Fogarty
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Publication number: 20180330718Abstract: A speech recognition system includes an input device to receive voice sounds, one or more processors, and one or more storage devices storing parameters and program modules including instructions executable by the one or more processors.Type: ApplicationFiled: May 11, 2017Publication date: November 15, 2018Applicant: Mitsubishi Electric Research Laboratories, Inc.Inventors: Takaaki Hori, Shinji Watanabe, John Hershey
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Publication number: 20180189572Abstract: A system for generating a word sequence includes one or more processors in connection with a memory and one or more storage devices storing instructions causing operations that include receiving first and second input vectors, extracting first and second feature vectors, estimating a first set of weights and a second set of weights, calculating a first content vector from the first set of weights and the first feature vectors, and calculating a second content vector, transforming the first content vector into a first modal content vector having a predetermined dimension and transforming the second content vector into a second modal content vector having the predetermined dimension, estimating a set of modal attention weights, generating a weighted content vector having the predetermined dimension from the set of modal attention weights and the first and second modal content vectors, and generating a predicted word using the sequence generator.Type: ApplicationFiled: March 29, 2017Publication date: July 5, 2018Applicant: Mitsubishi Electric Research Laboratories, Inc.Inventors: Chiori Hori, Takaaki Hori, John Hershey, Tim Marks
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Publication number: 20180157743Abstract: A method for performing multi-label classification includes extracting a feature vector from an input vector including input data by a feature extractor, determining, by a label predictor, a relevant vector including relevant labels having relevant scores based on the feature vector, updating a binary masking vector by masking pre-selected labels having been selected in previous label selections, applying the updated binary masking vector to the relevant vector such that the relevant label vector is updated to exclude the pre-selected labels from the relevant labels, and selecting a relevant label from the updated relevant label vector based on the relevant scores of the updated relevant label vector.Type: ApplicationFiled: December 7, 2016Publication date: June 7, 2018Applicant: Mitsubishi Electric Research Laboratories, Inc.Inventors: Takaaki Hori, Chiori Hori, Shinji Watanabe, John Hershey, Bret Harsham, Jonathan Le Roux
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Patent number: 9881631Abstract: A method transforms a noisy audio signal to an enhanced audio signal, by first acquiring the noisy audio signal from an environment. The noisy audio signal is processed by an enhancement network having network parameters to jointly produce a magnitude mask and a phase estimate. Then, the magnitude mask and the phase estimate are used to obtain the enhanced audio signal.Type: GrantFiled: February 12, 2015Date of Patent: January 30, 2018Assignee: Mitsubishi Electric Research Laboratories, Inc.Inventors: Hakan Erdogan, John Hershey, Shinji Watanabe, Jonathan Le Roux
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Patent number: 9842106Abstract: A method and system processes utterances that are acquired either from an automatic speech recognition (ASR) system or text. The utterances have associated identities of each party, such as role A utterances and role B utterances. The information corresponding to utterances, such as word sequence and identity, are converted to features. Each feature is received in an input layer of a neural network (NN). A dimensionality of each feature is reduced, in a projection layer of the NN, to produce a reduced dimensional feature. The reduced dimensional feature is processed to provide probabilities of labels for the utterances.Type: GrantFiled: December 4, 2015Date of Patent: December 12, 2017Assignee: Mitsubishi Electric Research Laboratories, IncInventors: Chiori Hori, Takaaki Hori, Shinji Watanabe, John Hershey
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Publication number: 20170334542Abstract: A airborne vehicle comprising a fuselage, a folding wing-like structure which is movable from a stowed position to a deployed position, and a hinge mechanism which couples the folding wing-like structure to the fuselage in a manner so that the folding wing-like structure displaces and rotates during movement from the stowed position to the deployed position. The hinge mechanism is housed within an outer mold line of the fuselage and folding wing-like structure to decrease the signature of the airborne vehicle.Type: ApplicationFiled: May 23, 2016Publication date: November 23, 2017Applicant: The Boeing CompanyInventors: Daniel Christopher Stanley, John Hershey Fogarty
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Publication number: 20170221474Abstract: A method and for training a language model to reduce recognition errors, wherein the language model is a recurrent neural network language model (RNNLM) by first acquiring training samples. An automatic speech recognition system (ASR) is appled to the training samples to produce recognized words and probabilites of the recognized words, and an N-best list is selected from the recognized words based on the probabilities. determining word erros using reference data for hypotheses in the N-best list. The hypotheses are rescored using the RNNLM. Then, we determine gradients for the hypotheses using the word errors and gradients for words in the hypotheses. Lastly, parameters of the RNNLM are updated using a sum of the gradients.Type: ApplicationFiled: February 2, 2016Publication date: August 3, 2017Inventors: Takaaki Hori, Chiori Hori, Shinji Watanabe, John Hershey