Patents by Inventor Lani Fang Wu

Lani Fang Wu 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).

  • Sound source separation using convolutional mixing and a priori sound source knowledge
    Patent number: 7047189
    Abstract: Sound source separation, without permutation, using convolutional mixing independent component analysis based on a priori knowledge of the target sound source is disclosed. The target sound source can be a human speaker. The reconstruction filters used in the sound source separation take into account the a priori knowledge of the target sound source, such as an estimate the spectra of the target sound source. The filters may be generally constructed based on a speech recognition system. Matching the words of the dictionary of the speech recognition system to a reconstructed signal indicates whether proper separation has occurred. More specifically, the filters may be constructed based on a vector quantization codebook of vectors representing typical sound source patterns. Matching the vectors of the codebook to a reconstructed signal indicates whether proper separation has occurred. The vectors may be linear prediction vectors, among others.
    Type: Grant
    Filed: November 18, 2004
    Date of Patent: May 16, 2006
    Assignee: Microsoft Corporation
    Inventors: Alejandro Acero, Steven J. Altschuler, Lani Fang Wu
  • Sound source separation using convolutional mixing and a priori sound source knowledge
    Patent number: 6879952
    Abstract: Sound source separation, without permutation, using convolutional mixing independent component analysis based on a priori knowledge of the target sound source is disclosed. The target sound source can be a human speaker. The reconstruction filters used in the sound source separation take into account the a priori knowledge of the target sound source, such as an estimate the spectra of the target sound source. The filters may be generally constructed based on a speech recognition system. Matching the words of the dictionary of the speech recognition system to a reconstructed signal indicates whether proper separation has occurred. More specifically, the filters may be constructed based on a vector quantization codebook of vectors representing typical sound source patterns. Matching the vectors of the codebook to a reconstructed signal indicates whether proper separation has occurred. The vectors may be linear prediction vectors, among others.
    Type: Grant
    Filed: April 25, 2001
    Date of Patent: April 12, 2005
    Assignee: Microsoft Corporation
    Inventors: Alejandro Acero, Steven J. Altschuler, Lani Fang Wu
  • Sound source separation using convolutional mixing and a priori sound source knowledge
    Publication number: 20010037195
    Abstract: Sound source separation, without permutation, using convolutional mixing independent component analysis based on a priori knowledge of the target sound source is disclosed. The target sound source can be a human speaker. The reconstruction filters used in the sound source separation take into account the a priori knowledge of the target sound source, such as an estimate the spectra of the target sound source. The filters may be generally constructed based on a speech recognition system. Matching the words of the dictionary of the speech recognition system to a reconstructed signal indicates whether proper separation has occurred. More specifically, the filters may be constructed based on a vector quantization codebook of vectors representing typical sound source patterns. Matching the vectors of the codebook to a reconstructed signal indicates whether proper separation has occurred. The vectors may be linear prediction vectors, among others.
    Type: Application
    Filed: April 25, 2001
    Publication date: November 1, 2001
    Inventors: Alejandro Acero, Steven J. Altschuler, Lani Fang Wu