Patents by Inventor Angus William Sackfield

Angus William Sackfield 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: 20230075074
    Abstract: A system, method and computer product for combining audio tracks. In one example embodiment herein, the method comprises determining at least one music track that is musically compatible with a base music track, aligning those tracks in time, and combining the tracks. In one example embodiment herein, the tracks may be music tracks of different songs, the base music track can be an instrumental accompaniment track, and the at least one music track can be a vocal track. Also in one example embodiment herein, the determining is based on musical characteristics associated with at least one of the tracks, such as an acoustic feature vector distance between tracks, a likelihood of at least one track including a vocal component, a tempo, or musical key. Also, determining of musical compatibility can include determining at least one of a vertical musical compatibility or a horizontal musical compatibility among tracks.
    Type: Application
    Filed: September 9, 2022
    Publication date: March 9, 2023
    Applicant: Spotify AB
    Inventors: Juan José BOSCH VICENTE, Youn Jin KIM, Peter Milan Thomson SOBOT, Angus William SACKFIELD
  • Patent number: 11568256
    Abstract: A system, method and computer product for training a neural network system. The method comprises inputting an audio signal to the system to generate plural outputs f(X, ?). The audio signal includes one or more of vocal content and/or musical instrument content, and each output f(X, ?) corresponds to a respective one of the different content types. The method also comprises comparing individual outputs f(X, ?) of the neural network system to corresponding target signals. For each compared output f(X, ?), at least one parameter of the system is adjusted to reduce a result of the comparing performed for the output f(X, ?), to train the system to estimate the different content types. In one example embodiment, the system comprises a U-Net architecture. After training, the system can estimate various different types of vocal and/or instrument components of an audio signal, depending on which type of component(s) the system is trained to estimate.
    Type: Grant
    Filed: March 18, 2021
    Date of Patent: January 31, 2023
    Assignee: Spotify AB
    Inventors: Andreas Simon Thore Jansson, Angus William Sackfield, Ching Chuan Sung, Rachel M. Bittner
  • Patent number: 11475867
    Abstract: A system, method and computer product for combining audio tracks. In one example embodiment herein, the method comprises determining at least one music track that is musically compatible with a base music track, aligning those tracks in time, and combining the tracks. In one example embodiment herein, the tracks may be music tracks of different songs, the base music track can be an instrumental accompaniment track, and the at least one music track can be a vocal track. Also in one example embodiment herein, the determining is based on musical characteristics associated with at least one of the tracks, such as an acoustic feature vector distance between tracks, a likelihood of at least one track including a vocal component, a tempo, or musical key. Also, determining of musical compatibility can include determining at least one of a vertical musical compatibility or a horizontal musical compatibility among tracks.
    Type: Grant
    Filed: December 27, 2019
    Date of Patent: October 18, 2022
    Assignee: Spotify AB
    Inventors: Juan José Bosch Vicente, Youn Jin Kim, Peter Milan Thomson Sobot, Angus William Sackfield
  • Patent number: 11182119
    Abstract: A system and methods for acquiring cadence and selecting a song version based on the acquired cadence are disclosed. If the system detects a new cadence, then a new song version that corresponds to the new cadence can be played. The new song version playback can start in a corresponding position as the location of playback in a currently-playing song version. Each related song version shares one or more characteristics, such as melody, but is different in at least one characteristic, such as tempo.
    Type: Grant
    Filed: January 15, 2020
    Date of Patent: November 23, 2021
    Assignee: Spotify AB
    Inventors: Sten Garmark, Dariusz Dziuk, Mateo Rando, Angus William Sackfield
  • Publication number: 20210279588
    Abstract: A system, method and computer product for training a neural network system. The method comprises inputting an audio signal to the system to generate plural outputs f(X, ?). The audio signal includes one or more of vocal content and/or musical instrument content, and each output f(X, ?) corresponds to a respective one of the different content types. The method also comprises comparing individual outputs f(X, ?) of the neural network system to corresponding target signals. For each compared output f(X, ?), at least one parameter of the system is adjusted to reduce a result of the comparing performed for the output f(X, ?), to train the system to estimate the different content types. In one example embodiment, the system comprises a U-Net architecture. After training, the system can estimate various different types of vocal and/or instrument components of an audio signal, depending on which type of component(s) the system is trained to estimate.
    Type: Application
    Filed: March 18, 2021
    Publication date: September 9, 2021
    Applicant: Spotify AB
    Inventors: Andreas Simon Thore Jansson, Angus William Sackfield, Ching Chuan Sung, Rachel M. Bittner
  • Publication number: 20210256995
    Abstract: A system, method and computer product for training a neural network system. The method comprises applying an audio signal to the neural network system, the audio signal including a vocal component and a non-vocal component. The method also comprises comparing an output of the neural network system to a target signal, and adjusting at least one parameter of the neural network system to reduce a result of the comparing, for training the neural network system to estimate one of the vocal component and the non-vocal component. In one example embodiment, the system comprises a U-Net architecture. After training, the system can estimate vocal or instrumental components of an audio signal, depending on which type of component the system is trained to estimate.
    Type: Application
    Filed: December 28, 2020
    Publication date: August 19, 2021
    Inventors: Andreas Simon Thore JANSSON, Angus William Sackfield, Ching Chuan Sung
  • Publication number: 20210256994
    Abstract: A system, method and computer product for training a neural network system. The method comprises applying an audio signal to the neural network system, the audio signal including a vocal component and a non-vocal component. The method also comprises comparing an output of the neural network system to a target signal, and adjusting at least one parameter of the neural network system to reduce a result of the comparing, for training the neural network system to estimate one of the vocal component and the non-vocal component. In one example embodiment, the system comprises a U-Net architecture. After training, the system can estimate vocal or instrumental components of an audio signal, depending on which type of component the system is trained to estimate.
    Type: Application
    Filed: December 28, 2020
    Publication date: August 19, 2021
    Applicant: Spotify AB
    Inventors: Andreas Simon Thore JANSSON, Angus William Sackfield, Ching Chuan Sung
  • Publication number: 20210201863
    Abstract: A system, method and computer product for combining audio tracks. In one example embodiment herein, the method comprises determining at least one music track that is musically compatible with a base music track, aligning those tracks in time, and combining the tracks. In one example embodiment herein, the tracks may be music tracks of different songs, the base music track can be an instrumental accompaniment track, and the at least one music track can be a vocal track. Also in one example embodiment herein, the determining is based on musical characteristics associated with at least one of the tracks, such as an acoustic feature vector distance between tracks, a likelihood of at least one track including a vocal component, a tempo, or musical key. Also, determining of musical compatibility can include determining at least one of a vertical musical compatibility or a horizontal musical compatibility among tracks.
    Type: Application
    Filed: December 27, 2019
    Publication date: July 1, 2021
    Inventors: Juan José BOSCH VICENTE, Youn Jin KIM, Peter Milan Thomson SOBOT, Angus William SACKFIELD
  • Patent number: 10991385
    Abstract: A system, method and computer product for estimating a component of a provided audio signal. The method comprises converting the provided audio signal to an image, processing the image with a neural network trained to estimate one of vocal content and instrumental content, and storing a spectral mask output from the neural network as a result of the image being processed by the neural network. The neural network is a U-Net. The method also comprises providing the spectral mask to a client media playback device, which applies the spectral mask to a spectrogram of the provided audio signal, to provide a masked spectrogram. The media playback device also transforms the masked spectrogram to an audio signal, and plays back that audio signal via an output user interface.
    Type: Grant
    Filed: October 19, 2018
    Date of Patent: April 27, 2021
    Assignee: Spotify AB
    Inventors: Andreas Simon Thore Jansson, Angus William Sackfield, Ching Chuan Sung, David Rubinstein
  • Patent number: 10977555
    Abstract: A system, method and computer product for training a neural network system. The method comprises inputting an audio signal to the system to generate plural outputs f(X, ?). The audio signal includes one or more of vocal content and/or musical instrument content, and each output f(X, ?) corresponds to a respective one of the different content types. The method also comprises comparing individual outputs f(X, ?) of the neural network system to corresponding target signals. For each compared output f(X, ?), at least one parameter of the system is adjusted to reduce a result of the comparing performed for the output f(X, ?), to train the system to estimate the different content types. In one example embodiment, the system comprises a U-Net architecture. After training, the system can estimate various different types of vocal and/or instrument components of an audio signal, depending on which type of component(s) the system is trained to estimate.
    Type: Grant
    Filed: July 25, 2019
    Date of Patent: April 13, 2021
    Assignee: Spotify AB
    Inventors: Andreas Simon Thore Jansson, Angus William Sackfield, Ching Chuan Sung, Rachel M. Bittner
  • Patent number: 10923142
    Abstract: A system, method and computer product for training a neural network system. The method comprises applying an audio signal to the neural network system, the audio signal including a vocal component and a non-vocal component. The method also comprises comparing an output of the neural network system to a target signal, and adjusting at least one parameter of the neural network system to reduce a result of the comparing, for training the neural network system to estimate one of the vocal component and the non-vocal component. In one example embodiment, the system comprises a U-Net architecture. After training, the system can estimate vocal or instrumental components of an audio signal, depending on which type of component the system is trained to estimate.
    Type: Grant
    Filed: January 8, 2019
    Date of Patent: February 16, 2021
    Assignee: Spotify AB
    Inventors: Andreas Simon Thore Jansson, Angus William Sackfield, Ching Chuan Sung
  • Patent number: 10923141
    Abstract: A system, method and computer product for training a neural network system. The method comprises applying an audio signal to the neural network system, the audio signal including a vocal component and a non-vocal component. The method also comprises comparing an output of the neural network system to a target signal, and adjusting at least one parameter of the neural network system to reduce a result of the comparing, for training the neural network system to estimate one of the vocal component and the non-vocal component. In one example embodiment, the system comprises a U-Net architecture. After training, the system can estimate vocal or instrumental components of an audio signal, depending on which type of component the system is trained to estimate.
    Type: Grant
    Filed: August 6, 2018
    Date of Patent: February 16, 2021
    Assignee: Spotify AB
    Inventors: Andreas Simon Thore Jansson, Angus William Sackfield, Ching Chuan Sung
  • Publication number: 20200150920
    Abstract: A system and methods for acquiring cadence and selecting a song version based on the acquired cadence are disclosed. If the system detects a new cadence, then a new song version that corresponds to the new cadence can be played. The new song version playback can start in a corresponding position as the location of playback in a currently-playing song version. Each related song version shares one or more characteristics, such as melody, but is different in at least one characteristic, such as tempo.
    Type: Application
    Filed: January 15, 2020
    Publication date: May 14, 2020
    Applicant: Spotify AB
    Inventors: Sten Garmark, Dariusz Dziuk, Mateo Rando, Angus William Sackfield
  • Patent number: 10572219
    Abstract: A system and methods for acquiring cadence and selecting a song version based on the acquired cadence are disclosed. If the system detects a new cadence, then a new song version that corresponds to the new cadence can be played. The new song version playback can start in a corresponding position as the location of playback in a currently-playing song version. Each related song version shares one or more characteristics, such as melody, but is different in at least one characteristic, such as tempo.
    Type: Grant
    Filed: February 25, 2019
    Date of Patent: February 25, 2020
    Assignee: SPOTIFY AB
    Inventors: Sten Garmark, Dariusz Dziuk, Mateo Rando, Angus William Sackfield
  • Publication number: 20200043518
    Abstract: A system, method and computer product for training a neural network system. The method comprises applying an audio signal to the neural network system, the audio signal including a vocal component and a non-vocal component. The method also comprises comparing an output of the neural network system to a target signal, and adjusting at least one parameter of the neural network system to reduce a result of the comparing, for training the neural network system to estimate one of the vocal component and the non-vocal component. In one example embodiment, the system comprises a U-Net architecture. After training, the system can estimate vocal or instrumental components of an audio signal, depending on which type of component the system is trained to estimate.
    Type: Application
    Filed: January 8, 2019
    Publication date: February 6, 2020
    Applicant: Spotify AB
    Inventors: Andreas Simon Thore JANSSON, Angus William Sackfield, Ching Chuan Sung
  • Publication number: 20200042879
    Abstract: A system, method and computer product for training a neural network system. The method comprises inputting an audio signal to the system to generate plural outputs f(X, ?). The audio signal includes one or more of vocal content and/or musical instrument content, and each output f(X, ?) corresponds to a respective one of the different content types. The method also comprises comparing individual outputs f(X, ?) of the neural network system to corresponding target signals. For each compared output f(X, ?), at least one parameter of the system is adjusted to reduce a result of the comparing performed for the output f(X, ?), to train the system to estimate the different content types. In one example embodiment, the system comprises a U-Net architecture. After training, the system can estimate various different types of vocal and/or instrument components of an audio signal, depending on which type of component(s) the system is trained to estimate.
    Type: Application
    Filed: July 25, 2019
    Publication date: February 6, 2020
    Inventors: Andreas Simon Thore Jansson, Angus William Sackfield, Ching Chuan Sung, Rachel M. Bittner
  • Publication number: 20200043516
    Abstract: A system, method and computer product for training a neural network system. The method comprises applying an audio signal to the neural network system, the audio signal including a vocal component and a non-vocal component. The method also comprises comparing an output of the neural network system to a target signal, and adjusting at least one parameter of the neural network system to reduce a result of the comparing, for training the neural network system to estimate one of the vocal component and the non-vocal component. In one example embodiment, the system comprises a U-Net architecture. After training, the system can estimate vocal or instrumental components of an audio signal, depending on which type of component the system is trained to estimate.
    Type: Application
    Filed: August 6, 2018
    Publication date: February 6, 2020
    Applicant: Spotify AB
    Inventors: Andreas Simon Thore JANSSON, Angus William Sackfield, Ching Chuan Sung
  • Publication number: 20190250880
    Abstract: A system and methods for acquiring cadence and selecting a song version based on the acquired cadence are disclosed. If the system detects a new cadence, then a new song version that corresponds to the new cadence can be played. The new song version playback can start in a corresponding position as the location of playback in a currently-playing song version. Each related song version shares one or more characteristics, such as melody, but is different in at least one characteristic, such as tempo.
    Type: Application
    Filed: February 25, 2019
    Publication date: August 15, 2019
    Inventors: Sten Garmark, Dariusz Dziuk, Mateo Rando, Angus William Sackfield
  • Patent number: 10255036
    Abstract: A system and methods for acquiring cadence and selecting a song version based on the acquired cadence are disclosed. If the system detects a new cadence, then a new song version that corresponds to the new cadence can be played. The new song version playback can start in a corresponding position as the location of playback in a currently-playing song version. Each related song version shares one or more characteristics, such as melody, but is different in at least one characteristic, such as tempo.
    Type: Grant
    Filed: February 20, 2018
    Date of Patent: April 9, 2019
    Assignee: SPOTIFY AB
    Inventors: Sten Garmark, Dariusz Dziuk, Mateo Rando, Angus William Sackfield
  • Publication number: 20180239580
    Abstract: A system and methods for acquiring cadence and selecting a song version based on the acquired cadence are disclosed. If the system detects a new cadence, then a new song version that corresponds to the new cadence can be played. The new song version playback can start in a corresponding position as the location of playback in a currently-playing song version. Each related song version shares one or more characteristics, such as melody, but is different in at least one characteristic, such as tempo.
    Type: Application
    Filed: February 20, 2018
    Publication date: August 23, 2018
    Applicant: Spotify AB
    Inventors: Sten Garmark, Dariusz Dziuk, Mateo Rando, Angus William Sackfield