Patents by Inventor Daniele Giacobello

Daniele Giacobello 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).

  • Publication number: 20210074317
    Abstract: Systems and methods for suppressing noise and detecting voice input in a multi-channel audio signal captured by a plurality of microphones include (i) capturing a first audio signal via a first microphone and a second audio signal via a second microphone, wherein the first and second audio signals respectively comprises first and second noise content from a noise source; (ii) identifying the first noise content in the first audio signal; (iii) using the identified first noise content to determine an estimated noise content captured by the plurality of microphones; (iv) using the estimated noise content to suppress the first and second noise content in the first and second audio signals; (v) combining the suppressed first and second audio signals into a third audio signal; and (vi) determining that the third audio signal includes a voice input comprising a wake word.
    Type: Application
    Filed: November 23, 2020
    Publication date: March 11, 2021
    Inventors: Saeed Bagheri Sereshki, Daniele Giacobello
  • Patent number: 10847178
    Abstract: Systems and methods for suppressing noise and detecting voice input in a multi-channel audio signal captured by a plurality of microphones include (i) capturing a first audio signal via a first microphone and a second audio signal via a second microphone, wherein the first and second audio signals respectively comprises first and second noise content from a noise source; (ii) identifying the first noise content in the first audio signal; (iii) using the identified first noise content to determine an estimated noise content captured by the plurality of microphones; (iv) using the estimated noise content to suppress the first and second noise content in the first and second audio signals; (v) combining the suppressed first and second audio signals into a third audio signal; and (vi) determining that the third audio signal includes a voice input comprising a wake word.
    Type: Grant
    Filed: May 18, 2018
    Date of Patent: November 24, 2020
    Assignee: Sonos, Inc.
    Inventors: Saeed Bagheri Sereshki, Daniele Giacobello
  • Publication number: 20200321021
    Abstract: Systems and methods for suppressing noise and detecting voice input in a multi-channel audio signal captured by two or more network microphone devices include receiving an instruction to process one or more audio signals captured by a first network microphone device and after receiving the instruction (i) disabling at least a first microphone of a plurality of microphones of a second network microphone device, (ii) capturing a first audio signal via a second microphone of the plurality of microphones, (iii) receiving over a network interface of the second network microphone device a second audio signal captured via at least a third microphone of the first network microphone device, (iv) using estimated noise content to suppress first and second noise content in the first and second audio signals, (v) combining the suppressed first and second audio signals into a third audio signal, and (vi) determining that the third audio signal includes a voice input comprising a wake word.
    Type: Application
    Filed: June 22, 2020
    Publication date: October 8, 2020
    Inventors: Saeed Bagheri Sereshki, Daniele Giacobello
  • Patent number: 10692518
    Abstract: Systems and methods for suppressing noise and detecting voice input in a multi-channel audio signal captured by two or more network microphone devices include receiving an instruction to process one or more audio signals captured by a first network microphone device and after receiving the instruction (i) disabling at least a first microphone of a plurality of microphones of a second network microphone device, (ii) capturing a first audio signal via a second microphone of the plurality of microphones, (iii) receiving over a network interface of the second network microphone device a second audio signal captured via at least a third microphone of the first network microphone device, (iv) using estimated noise content to suppress first and second noise content in the first and second audio signals, (v) combining the suppressed first and second audio signals into a third audio signal, and (vi) determining that the third audio signal includes a voice input comprising a wake word.
    Type: Grant
    Filed: September 29, 2018
    Date of Patent: June 23, 2020
    Assignee: Sonos, Inc.
    Inventors: Saeed Bagheri Sereshki, Daniele Giacobello
  • Publication number: 20200125162
    Abstract: Systems, methods, and devices with reduced power consumption in network microphone devices. In one embodiment, a network microphone device is configured to perform a method that includes (i) capturing audio content; (ii) using a first algorithm to perform a keyword detection process for determining whether the audio content includes a keyword; (iii) responsive to determining that the audio content includes the keyword, using a second, more computationally intensive algorithm to perform a wake-word detection process for determining whether the audio content includes a wake word; and (iv) responsive to performing the wake-word detection process, (a) causing a voice service corresponding to the wake word to process the audio content if the wake-word detection process confirms that the audio content includes the wake word or (b) ceasing performance of the wake-word detection process if the wake-word detection process disconfirms that the audio content includes the wake word.
    Type: Application
    Filed: October 23, 2018
    Publication date: April 23, 2020
    Inventors: Nick D'Amato, Daniele Giacobello, Joachim Fainberg, Klaus Hartung
  • Publication number: 20200105256
    Abstract: Systems and methods for media playback via a media playback system include capturing sound data via a network microphone device and identifying a candidate wake word in the sound data. Based on identification of the candidate wake word in the sound data, the system selects a first wake-word engine from a plurality of wake-word engines. Via the first wake-word engine, the system analyzes the sound data to detect a confirmed wake word, and, in response to detecting the confirmed wake word, transmits a voice utterance of the sound data to one or more remote computing devices associated with a voice assistant service.
    Type: Application
    Filed: September 28, 2018
    Publication date: April 2, 2020
    Inventors: Joachim Fainberg, Daniele Giacobello, Klaus Hartung
  • Publication number: 20200105295
    Abstract: Systems and methods for suppressing noise and detecting voice input in a multi-channel audio signal captured by two or more network microphone devices include receiving an instruction to process one or more audio signals captured by a first network microphone device and after receiving the instruction (i) disabling at least a first microphone of a plurality of microphones of a second network microphone device, (ii) capturing a first audio signal via a second microphone of the plurality of microphones, (iii) receiving over a network interface of the second network microphone device a second audio signal captured via at least a third microphone of the first network microphone device, (iv) using estimated noise content to suppress first and second noise content in the first and second audio signals, (v) combining the suppressed first and second audio signals into a third audio signal, and (vi) determining that the third audio signal includes a voice input comprising a wake word.
    Type: Application
    Filed: September 29, 2018
    Publication date: April 2, 2020
    Inventors: Saeed Bagheri Sereshki, Daniele Giacobello
  • Publication number: 20200043507
    Abstract: Example techniques involve noise-robust acoustic echo cancellation. An example implementation may involve causing one or more speakers of the playback device to play back audio content and while the audio content is playing back, capturing, via the one or more microphones, audio within an acoustic environment that includes the audio playback. The example implementation may involve determining measured and reference signals in the STFT domain. During each nth iteration of an acoustic echo canceller (AEC): the implementation may involve determining a frame of an output signal by generating a frame of a model signal by passing a frame of the reference signal through an instance of an adaptive filter and then redacting the nth frame of the model signal from an nth frame of the measured signal. The implementation may further involve determining an instance of the adaptive filter for a next iteration of the AEC.
    Type: Application
    Filed: October 14, 2019
    Publication date: February 6, 2020
    Inventor: Daniele Giacobello
  • Publication number: 20190355384
    Abstract: Systems and methods for suppressing noise and detecting voice input in a multi-channel audio signal captured by a plurality of microphones include (i) capturing a first audio signal via a first microphone and a second audio signal via a second microphone, wherein the first and second audio signals respectively comprises first and second noise content from a noise source; (ii) identifying the first noise content in the first audio signal; (iii) using the identified first noise content to determine an estimated noise content captured by the plurality of microphones; (iv) using the estimated noise content to suppress the first and second noise content in the first and second audio signals; (v) combining the suppressed first and second audio signals into a third audio signal; and (vi) determining that the third audio signal includes a voice input comprising a wake word.
    Type: Application
    Filed: May 18, 2018
    Publication date: November 21, 2019
    Inventors: Saeed Bagheri Sereshki, Daniele Giacobello
  • Patent number: 10446165
    Abstract: Example techniques involve noise-robust acoustic echo cancellation. An example implementation may involve causing one or more speakers of the playback device to play back audio content and while the audio content is playing back, capturing, via the one or more microphones, audio within an acoustic environment that includes the audio playback. The example implementation may involve determining measured and reference signals in the STFT domain. During each nth iteration of an acoustic echo canceller (AEC): the implementation may involve determining a frame of an output signal by generating a frame of a model signal by passing a frame of the reference signal through an instance of an adaptive filter and then redacting the nth frame of the model signal from an nth frame of the measured signal. The implementation may further involve determining an instance of the adaptive filter for a next iteration of the AEC.
    Type: Grant
    Filed: September 27, 2017
    Date of Patent: October 15, 2019
    Assignee: Sonos, Inc.
    Inventor: Daniele Giacobello
  • Publication number: 20190096419
    Abstract: Example techniques involve noise-robust acoustic echo cancellation. An example implementation may involve causing one or more speakers of the playback device to play back audio content and while the audio content is playing back, capturing, via the one or more microphones, audio within an acoustic environment that includes the audio playback. The example implementation may involve determining measured and reference signals in the STFT domain. During each nth iteration of an acoustic echo canceller (AEC): the implementation may involve determining a frame of an output signal by generating a frame of a model signal by passing a frame of the reference signal through an instance of an adaptive filter and then redacting the nth frame of the model signal from an nth frame of the measured signal. The implementation may further involve determining an instance of the adaptive filter for a next iteration of the AEC.
    Type: Application
    Filed: September 27, 2017
    Publication date: March 28, 2019
    Inventor: Daniele Giacobello
  • Publication number: 20180277113
    Abstract: Disclosed herein are example techniques to identify a voice service to process a voice input. An example implementation may involve a network microphone device (NMD) receiving, via a microphone, voice data indicating a voice input. The NMD may identify, from among multiple voice services registered to a media playback system, a voice service to process the voice input and cause, via a network interface, the identified voice service to process the voice input.
    Type: Application
    Filed: March 26, 2018
    Publication date: September 27, 2018
    Inventors: Klaus Hartung, Daniele Giacobello
  • Patent number: 10074380
    Abstract: Method for performing speech enhancement using a Deep Neural Network (DNN)-based signal starts with training DNN offline by exciting a microphone using target training signal that includes signal approximation of clean speech. Loudspeaker is driven with a reference signal and outputs loudspeaker signal. Microphone then generates microphone signal based on at least one of: near-end speaker signal, ambient noise signal, or loudspeaker signal. Acoustic-echo-canceller (AEC) generates AEC echo-cancelled signal based on reference signal and microphone signal. Loudspeaker signal estimator generates estimated loudspeaker signal based on microphone signal and AEC echo-cancelled signal. DNN receives microphone signal, reference signal, AEC echo-cancelled signal, and estimated loudspeaker signal and generates a speech reference signal that includes signal statistics for residual echo or for noise.
    Type: Grant
    Filed: August 3, 2016
    Date of Patent: September 11, 2018
    Assignee: Apple Inc.
    Inventors: Jason Wung, Ramin Pishehvar, Daniele Giacobello, Joshua D. Atkins
  • Publication number: 20180040333
    Abstract: Method for performing speech enhancement using a Deep Neural Network (DNN)-based signal starts with training DNN offline by exciting a microphone using target training signal that includes signal approximation of clean speech. Loudspeaker is driven with a reference signal and outputs loudspeaker signal. Microphone then generates microphone signal based on at least one of: near-end speaker signal, ambient noise signal, or loudspeaker signal. Acoustic-echo-canceller (AEC) generates AEC echo-cancelled signal based on reference signal and microphone signal. Loudspeaker signal estimator generates estimated loudspeaker signal based on microphone signal and AEC echo-cancelled signal. DNN receives microphone signal, reference signal, AEC echo-cancelled signal, and estimated loudspeaker signal and generates a speech reference signal that includes signal statistics for residual echo or for noise.
    Type: Application
    Filed: August 3, 2016
    Publication date: February 8, 2018
    Inventors: Jason Wung, Ramin Pishehvar, Daniele Giacobello, Joshua D. Atkins
  • Patent number: 9633671
    Abstract: An echo canceller can be arranged to receive an input signal and to receive a reference signal. The echo canceller can subtract a linear component of the reference signal from the input signal. A noise suppressor can suppress non-linear effects of the reference signal in the input signal in correspondence with a large number of selectable parameters. Such suppression can be provided on a frequency-by-frequency basis, with a unique set of tunable parameters selected for each frequency. A degree of suppression provided by the noise suppressor can correspond to an estimate of residual echo remaining after the one or more linear components of the reference signal have been subtracted from the input signal, to an estimated double-talk probability, and to an estimated signal-to-noise ratio of near-end speech in the input signal for each respective frequency. A speech recognizer can receive a processed input signal from the noise suppressor.
    Type: Grant
    Filed: October 17, 2014
    Date of Patent: April 25, 2017
    Assignee: APPLE INC.
    Inventors: Daniele Giacobello, Jason Wung, Joshua Atkins, Ramin Pichevar, Raghavendra Prabhu
  • Publication number: 20160241955
    Abstract: Methods, systems, and apparatuses are described for improved multi-microphone source tracking and noise suppression. In multi-microphone devices and systems, frequency domain acoustic echo cancellation is performed on each microphone input, and microphone levels and sensitivity are normalized. Methods, systems, and apparatuses are also described for improved acoustic scene analysis and source tracking using steered null error transforms, on-line adaptive acoustic scene modeling, and speaker-dependent information. Switched super-directive beamforming reinforces desired audio sources and closed-form blocking matrices suppress desired audio sources based on spatial information derived from microphone pairings. Underlying statistics are tracked and used to updated filters and models. Automatic detection of single-user and multi-user scenarios, and single-channel suppression using spatial information, non-spatial information, and residual echo are also described.
    Type: Application
    Filed: April 22, 2016
    Publication date: August 18, 2016
    Inventors: Jes Thyssen, Ashutosh Pandey, Bengt J. Borgstrom, Daniele Giacobello, Juin-Hwey Chen
  • Patent number: 9338551
    Abstract: Methods, systems, and apparatuses are described for improved multi-microphone source tracking and noise suppression. In multi-microphone devices and systems, frequency domain acoustic echo cancellation is performed on each microphone input, and microphone levels and sensitivity are normalized. Methods, systems, and apparatuses are also described for improved acoustic scene analysis and source tracking using steered null error transforms, on-line adaptive acoustic scene modeling, and speaker-dependent information. Switched super-directive beamforming reinforces desired audio sources and closed-form blocking matrices suppress desired audio sources based on spatial information derived from microphone pairings. Underlying statistics are tracked and used to updated filters and models. Automatic detection of single-user and multi-user scenarios, and single-channel suppression using spatial information, non-spatial information, and residual echo are also described.
    Type: Grant
    Filed: March 17, 2014
    Date of Patent: May 10, 2016
    Assignee: Broadcom Corporation
    Inventors: Jes Thyssen, Ashutosh Pandey, Bengt J. Borgstrom, Daniele Giacobello, Juin-Hwey Chen
  • Publication number: 20150112672
    Abstract: An echo canceller can be arranged to receive an input signal and to receive a reference signal. The echo canceller can subtract a linear component of the reference signal from the input signal. A noise suppressor can suppress non-linear effects of the reference signal in the input signal in correspondence with a large number of selectable parameters. Such suppression can be provided on a frequency-by-frequency basis, with a unique set of tunable parameters selected for each frequency. A degree of suppression provided by the noise suppressor can correspond to an estimate of residual echo remaining after the one or more linear components of the reference signal have been subtracted from the input signal, to an estimated double-talk probability, and to an estimated signal-to-noise ratio of near-end speech in the input signal for each respective frequency. A speech recognizer can receive a processed input signal from the noise suppressor.
    Type: Application
    Filed: October 17, 2014
    Publication date: April 23, 2015
    Inventors: Daniele Giacobello, Jason Wung, Joshua Atkins, Ramin Pichevar, Raghavendra Prabhu
  • Publication number: 20140286497
    Abstract: Methods, systems, and apparatuses are described for improved multi-microphone source tracking and noise suppression. In multi-microphone devices and systems, frequency domain acoustic echo cancellation is performed on each microphone input, and microphone levels and sensitivity are normalized. Methods, systems, and apparatuses are also described for improved acoustic scene analysis and source tracking using steered null error transforms, on-line adaptive acoustic scene modeling, and speaker-dependent information. Switched super-directive beamforming reinforces desired audio sources and closed-form blocking matrices suppress desired audio sources based on spatial information derived from microphone pairings. Underlying statistics are tracked and used to updated filters and models. Automatic detection of single-user and multi-user scenarios, and single-channel suppression using spatial information, non-spatial information, and residual echo are also described.
    Type: Application
    Filed: March 17, 2014
    Publication date: September 25, 2014
    Applicant: Broadcom Corporation
    Inventors: Jes Thyssen, Ashutosh Pandey, Bengt J. Borgstrom, Daniele Giacobello, Juin-Hwey Chen