Patents by Inventor Ivan Jelev Tashev

Ivan Jelev Tashev 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).

  • Patent number: 11012802
    Abstract: A computing system that facilitates decoding a spherical harmonics (SH) representation of a three-dimensional sound signal to a binaural sound signal is described herein. The computing system generates a binaural sound signal based upon the SH representation, a tapering window function that is selected based on an SH encoding order of the SH representation, and a coloration compensation filter that incorporates the tapering window function. The computing system causes the binaural sound signal to be played over at least two speakers.
    Type: Grant
    Filed: July 2, 2019
    Date of Patent: May 18, 2021
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Christoph Felix Hold, Hannes Gamper, Ville Topias Pulkki, Nikunj Raghuvanshi, Ivan Jelev Tashev
  • Patent number: 10984315
    Abstract: A facility for processing output from a network of mechanical sensors is described. The facility accesses time-series data outputted by the network of sensors. The facility applies to the accessed time-series data a trained autoencoder to obtain a version of the accessed time-series data in which noise present in the accessed time-series data is at least partially suppressed. The facility stores the obtained version of the accessed time-series data, such as in order to perform human activity recognition against the obtained version of the accessed time-series data.
    Type: Grant
    Filed: April 28, 2017
    Date of Patent: April 20, 2021
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Shuayb M Zarar, Ivan Jelev Tashev
  • Publication number: 20210006923
    Abstract: A computing system that facilitates decoding a spherical harmonics (SH) representation of a three-dimensional sound signal to a binaural sound signal is described herein. The computing system generates a binaural sound signal based upon the SH representation, a tapering window function that is selected based on an SH encoding order of the SH representation, and a coloration compensation filter that incorporates the tapering window function. The computing system causes the binaural sound signal to be played over at least two speakers.
    Type: Application
    Filed: July 2, 2019
    Publication date: January 7, 2021
    Inventors: Christoph Felix HOLD, Hannes GAMPER, Ville Topias PULKKI, Nikunj RAGHUVANSHI, Ivan Jelev TASHEV
  • Patent number: 10672414
    Abstract: Systems, methods, and computer-readable storage devices are disclosed for improved real-time audio processing. One method including: receiving audio data including a plurality of frames having a plurality of frequency bins; calculating, for each frequency bin, an approximate speech signal estimation based on the plurality of frames; calculating, for each approximate speech signal estimation, a clean speech estimation and at least one additional target including an ideal ratio mask using a trained neural network model; and calculating, for each frequency bin, a final clean speech estimation using the calculated at least one additional target including the calculated ideal ratio mask and the calculated clean speech estimation.
    Type: Grant
    Filed: April 13, 2018
    Date of Patent: June 2, 2020
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Ivan Jelev Tashev, Shuayb M Zarar, Yan-Hui Tu, Chin-Hui Lee, Han Zhao
  • Publication number: 20200035259
    Abstract: Systems, methods, and computer-readable storage devices are disclosed for improved audio feature discovery using a neural network. One method including: receiving a trained neural network model, the trained neural network configured to output an audio feature classification of audio data; deconstructing the trained neural network model to generate at least one saliency map, the at least one saliency map providing a successful classification of the audio feature; and extracting at least one visualization of the audio feature the trained neural network model relies on for classification based on the at least one saliency map.
    Type: Application
    Filed: July 27, 2018
    Publication date: January 30, 2020
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Etienne THUILLIER, Hannes GAMPER, Ivan Jelev TASHEV
  • Patent number: 10528147
    Abstract: An ultrasonic gesture recognition system is provided that recognizes gestures based on analysis of return signals of an ultrasonic pulse that is reflected from a gesture. The system transmits an ultrasonic chirp and samples a microphone array at sample intervals to collect a return signal for each microphone. The system then applies a beamforming technique to frequency domain representations of the return signals to generate an acoustic image with a beamformed return signal for multiple directions. The system then generates a feature image from the acoustic images to identify, for example, distance or depth from the microphone array to the gesture for each direction. The system then submits the feature image to a deep learning system to classify the gesture.
    Type: Grant
    Filed: June 30, 2017
    Date of Patent: January 7, 2020
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Ivan Jelev Tashev, Shuayb Zarar, Amit Das
  • Publication number: 20190318755
    Abstract: Systems, methods, and computer-readable storage devices are disclosed for improved real-time audio processing. One method including: receiving audio data including a plurality of frames having a plurality of frequency bins; calculating, for each frequency bin, an approximate speech signal estimation based on the plurality of frames; calculating, for each approximate speech signal estimation, a clean speech estimation and at least one additional target including an ideal ratio mask using a trained neural network model; and calculating, for each frequency bin, a final clean speech estimation using the calculated at least one additional target including the calculated ideal ratio mask and the calculated clean speech estimation.
    Type: Application
    Filed: April 13, 2018
    Publication date: October 17, 2019
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Ivan Jelev TASHEV, Shuayb M ZARAR, Yan-Hui TU, Chin-Hui LEE, Han ZHAO
  • Publication number: 20190318237
    Abstract: Systems, methods, and computer-readable storage devices are disclosed for improved real-time audio processing. One method including: constructing a deep neural network model, including a plurality of at least one-bit neurons, configured to output a predicted label of audio data, the plurality of at least one-bit neurons arranged in a plurality of layers, including at least one hidden layer, and being connected by a plurality of connections, each connection having at least a one-bit weight, wherein one or both of the plurality of at least one-bit neurons and the plurality of connections have a reduced bit precision; receiving a training data set, the training data set including audio data; training the deep neural network model using the training data set; and outputting a trained deep neural network model configured to output a predicted label of real-time audio data.
    Type: Application
    Filed: April 13, 2018
    Publication date: October 17, 2019
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Ivan Jelev TASHEV, Shuayb M ZARAR, Matthai PHILIPOSE, Jong HWAN KO
  • Patent number: 10276179
    Abstract: A system is provided that employs a statistical approach to semi-supervised speech enhancement with a low-order non-negative matrix factorization (“NMF”). The system enhances noisy speech based on multiple dictionaries with dictionary atoms derived from the same clean speech samples and generates an enhanced speech representation of the noisy speech by combining, for each dictionary, a clean speech representation of the noisy speech generated based on a NMF using the dictionary atoms of the dictionary. The system generates frequency-domain (“FD”) clean speech sample representations of the clean speech samples, for example, using a Fourier transform. To generate each dictionary, the system generates a dictionary-unique initialization of the dictionary atoms and the activations and performs a NMF of the FD clean speech samples.
    Type: Grant
    Filed: June 16, 2017
    Date of Patent: April 30, 2019
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Ivan Jelev Tashev, Shuayb M Zarar
  • Patent number: 10129684
    Abstract: Systems and methods of providing an audio signal are disclosed herein. In one embodiment, a method of delivering an audio signal from a device toward a user's ear includes, for example, transmitting a filtered audio signal from a transducer positioned at a location on the device that is longitudinally spaced apart from an entrance of an auditory canal of the user's ear when the device is worn on the user's head.
    Type: Grant
    Filed: February 9, 2017
    Date of Patent: November 13, 2018
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Hannes Gamper, Mark Richard Paul Thomas, Ivan Jelev Tashev, David Emerson Johnston
  • Publication number: 20180314937
    Abstract: A facility for processing output from a network of mechanical sensors is described. The facility accesses time-series data outputted by the network of sensors. The facility applies to the accessed time-series data a trained autoencoder to obtain a version of the accessed time-series data in which noise present in the accessed time-series data is at least partially suppressed. The facility stores the obtained version of the accessed time-series data, such as in order to perform human activity recognition against the obtained version of the accessed time-series data.
    Type: Application
    Filed: April 28, 2017
    Publication date: November 1, 2018
    Inventors: Shuayb M. Zarar, Ivan Jelev TASHEV
  • Publication number: 20180254050
    Abstract: A system is provided that employs a statistical approach to semi-supervised speech enhancement with a low-order non-negative matrix factorization (“NMF”). The system enhances noisy speech based on multiple dictionaries with dictionary atoms derived from the same clean speech samples and generates an enhanced speech representation of the noisy speech by combining, for each dictionary, a clean speech representation of the noisy speech generated based on a NMF using the dictionary atoms of the dictionary. The system generates frequency-domain (“FD”) clean speech sample representations of the clean speech samples, for example, using a Fourier transform. To generate each dictionary, the system generates a dictionary-unique initialization of the dictionary atoms and the activations and performs a NMF of the FD clean speech samples.
    Type: Application
    Filed: June 16, 2017
    Publication date: September 6, 2018
    Inventors: Ivan Jelev Tashev, Shuayb Zarar
  • Publication number: 20170300124
    Abstract: An ultrasonic gesture recognition system is provided that recognizes gestures based on analysis of return signals of an ultrasonic pulse that is reflected from a gesture. The system transmits an ultrasonic chirp and samples a microphone array at sample intervals to collect a return signal for each microphone. The system then applies a beamforming technique to frequency domain representations of the return signals to generate an acoustic image with a beamformed return signal for multiple directions. The system then generates a feature image from the acoustic images to identify, for example, distance or depth from the microphone array to the gesture for each direction. The system then submits the feature image to a deep learning system to classify the gesture.
    Type: Application
    Filed: June 30, 2017
    Publication date: October 19, 2017
    Inventors: Ivan Jelev TASHEV, Shuayb ZARAR, Amit DAS
  • Publication number: 20170156017
    Abstract: Systems and methods of providing an audio signal are disclosed herein. In one embodiment, a method of delivering an audio signal from a device toward a user's ear includes, for example, transmitting a filtered audio signal from a transducer positioned at a location on the device that is longitudinally spaced apart from an entrance of an auditory canal of the user's ear when the device is worn on the user's head.
    Type: Application
    Filed: February 9, 2017
    Publication date: June 1, 2017
    Inventors: Hannes Gamper, Mark Richard Paul Thomas, Ivan Jelev Tashev, David Emerson Johnston
  • Patent number: 9609436
    Abstract: Systems and methods of providing an audio signal are disclosed herein. In one embodiment, a method of producing an audio signal includes applying, for example, a head related transfer function (HRTF) and a transducer position compensation filter to an input audio signal to generate an enhanced audio signal configured to be transmitted toward an entrance of the user's ear from a transducer carried by a headset and spaced apart from the entrance to a user's ear.
    Type: Grant
    Filed: May 22, 2015
    Date of Patent: March 28, 2017
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Hannes Gamper, Mark Richard Paul Thomas, Ivan Jelev Tashev, David Emerson Johnson
  • Publication number: 20160345095
    Abstract: Systems and methods of providing an audio signal are disclosed herein. In one embodiment, a method of producing an audio signal includes applying, for example, a head related transfer function (HRTF) and a transducer position compensation filter to an input audio signal to generate an enhanced audio signal configured to be transmitted toward an entrance of the user's ear from a transducer carried by a headset and spaced apart from the entrance to a user's ear.
    Type: Application
    Filed: May 22, 2015
    Publication date: November 24, 2016
    Inventors: Hannes Gamper, Mark Richard Paul Thomas, Ivan Jelev Tashev, David Emerson Johnston
  • Patent number: 9264807
    Abstract: A multichannel acoustic echo reduction system is described herein. The system includes an acoustic echo canceller (AEC) component having a fixed filter for each respective combination of loudspeaker and microphone signals and having an adaptive filter for each microphone signal. For each microphone signal, the AEC component modifies the microphone signal to reduce contributions from the outputs of the loudspeakers based at least in part on the respective adaptive filter associated with the microphone signal and the set of fixed filters associated with the respective microphone signal.
    Type: Grant
    Filed: January 23, 2013
    Date of Patent: February 16, 2016
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Ivan Jelev Tashev, Alejandro Acero, Nilesh Madhu
  • Patent number: 8401206
    Abstract: Described is a audio signal processing technology in which an adaptive beamformer processes input signals from microphones based on an estimate received from a pre-filter. The adaptive beamformer may compute its parameters (e.g., weights) for each frame based on the estimate, via a magnitude-domain objective function or log-magnitude-domain objective function. The pre-filter may include a time invariant beamformer and/or a non-linear spatial filter, and/or may include a spectral filter. The computed parameters may be adjusted based on a constraint, which may be selectively applied only at desired times.
    Type: Grant
    Filed: January 15, 2009
    Date of Patent: March 19, 2013
    Assignee: Microsoft Corporation
    Inventors: Michael Lewis Seltzer, Ivan Jelev Tashev
  • Patent number: 8385557
    Abstract: A multichannel acoustic echo reduction system is described herein. The system includes an acoustic echo canceller (AEC) component having a fixed filter for each respective combination of loudspeaker and microphone signals and having an adaptive filter for each microphone signal. For each microphone signal, the AEC component modifies the microphone signal to reduce contributions from the outputs of the loudspeakers based at least in part on the respective adaptive filter associated with the microphone signal and the set of fixed filters associated with the respective microphone signal.
    Type: Grant
    Filed: June 19, 2008
    Date of Patent: February 26, 2013
    Assignee: Microsoft Corporation
    Inventors: Ivan Jelev Tashev, Alejandro Acero, Nilesh Madhu
  • Publication number: 20100177908
    Abstract: Described is a audio signal processing technology in which an adaptive beamformer processes input signals from microphones based on an estimate received from a pre-filter. The adaptive beamformer may compute its parameters (e.g., weights) for each frame based on the estimate, via a magnitude-domain objective function or log-magnitude-domain objective function. The pre-filter may include a time invariant beamformer and/or a non-linear spatial filter, and/or may include a spectral filter. The computed parameters may be adjusted based on a constraint, which may be selectively applied only at desired times.
    Type: Application
    Filed: January 15, 2009
    Publication date: July 15, 2010
    Applicant: Microsoft Corporation
    Inventors: Michael Lewis Seltzer, Ivan Jelev Tashev