Patents by Inventor Emma JOKINEN

Emma JOKINEN 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: 10692510
    Abstract: It is shown an encoder for encoding an audio signal with reduced background noise using linear predictive coding. The encoder includes a background noise estimator configured to estimate background noise of the audio signal, a background noise reducer configured to generate background noise reduced audio signal by subtracting the estimated background noise of the audio signal from the audio signal, and a predictor configured to subject the audio signal to linear prediction analysis to obtain a first set of linear prediction filter (LPC) coefficients and to subject the background noise reduced audio signal to linear prediction analysis to obtain a second set of linear prediction filter (LPC) coefficients. Furthermore, the encoder includes an analysis filter composed of a cascade of time-domain filters controlled by the obtained first set of LPC coefficients and the obtained second set of LPC coefficients.
    Type: Grant
    Filed: March 14, 2018
    Date of Patent: June 23, 2020
    Assignee: Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V.
    Inventors: Johannes Fischer, Tom Bäckström, Emma Jokinen
  • Patent number: 10672411
    Abstract: An audio encoder for providing an encoded representation on the basis of an audio signal, wherein the audio encoder is configured to obtain a noise information describing a noise included in the audio signal, and wherein the audio encoder is configured to adaptively encode the audio signal in dependence on the noise information, such that encoding accuracy is higher for parts of the audio signal that are less affected by the noise included in the audio signal than for parts of the audio signal that are more affected by the noise included in the audio signal.
    Type: Grant
    Filed: October 4, 2017
    Date of Patent: June 2, 2020
    Assignee: Fraunhofer-Gesellschaft zur Foerderung der angewandten Forschung e.V.
    Inventors: Tom Baeckstroem, Emma Jokinen
  • Publication number: 20180204580
    Abstract: It is shown an encoder for encoding an audio signal with reduced background noise using linear predictive coding. The encoder includes a background noise estimator configured to estimate background noise of the audio signal, a background noise reducer configured to generate background noise reduced audio signal by subtracting the estimated background noise of the audio signal from the audio signal, and a predictor configured to subject the audio signal to linear prediction analysis to obtain a first set of linear prediction filter (LPC) coefficients and to subject the background noise reduced audio signal to linear prediction analysis to obtain a second set of linear prediction filter (LPC) coefficients. Furthermore, the encoder includes an analysis filter composed of a cascade of time-domain filters controlled by the obtained first set of LPC coefficients and the obtained second set of LPC coefficients.
    Type: Application
    Filed: March 14, 2018
    Publication date: July 19, 2018
    Inventors: Johannes FISCHER, Tom BÄCKSTRÖM, Emma JOKINEN
  • Publication number: 20180033444
    Abstract: An audio encoder for providing an encoded representation on the basis of an audio signal, wherein the audio encoder is configured to obtain a noise information describing a noise included in the audio signal, and wherein the audio encoder is configured to adaptively encode the audio signal in dependence on the noise information, such that encoding accuracy is higher for parts of the audio signal that are less affected by the noise included in the audio signal than for parts of the audio signal that are more affected by the noise included in the audio signal.
    Type: Application
    Filed: October 4, 2017
    Publication date: February 1, 2018
    Inventors: Tom BAECKSTROEM, Emma JOKINEN