EMBEDDED AUDITORY SYSTEM AND METHOD FOR PROCESSING VOICE SIGNAL

• US 20110144988A1
• Filed: 08/16/2010
• Published: 06/16/2011
• Est. Priority Date: 12/11/2009
• Status: Abandoned Application

• Current Assignee: Korea Advanced Institute of Science and Technology
• Original Assignee: Korea Advanced Institute of Science and Technology
• Inventors: Cho, Nam Ik, Lee, Byung-Gi, Kim, Hyung Soon, Kim, Munsang, Choi, JongSuk
• Application Number:
  US12/857,059
• Publication Number:
  US 20110144988A1
• Time in Patent Office: Days
• US Class Current: 704/233
• CPC Class Codes: G10L 2015/088 Word spotting
• CPC Class Codes: G10L 2021/02166 Microphone arrays; Beamforming
• CPC Class Codes: G10L 2021/02168 the estimation exclusively taking place during speech pauses
• CPC Class Codes: G10L 21/0208 Noise filtering
• CPC Class Codes: G10L 25/78 Detection of presence or absence of voice signals switching of direction of transmission by voice frequency in two-way loud-speaking telephone systems H04M9/10

Abstract

An embedded auditory system includes a voice detecting unit for receiving a voice signal as an input and dividing the voice signal into a voice section and a non-voice section; a noise removing unit for removing a noise in the voice section of the voice signal using noise information in the non-voice section of the voice signal; and a keyword spotting unit for extracting a feature vector from the voice signal noise-removed by the noise removing unit and detecting a keyword from the voice section of the voice signal using the feature vector. A method for processing a voice signal includes receiving a voice signal as an input and dividing the voice signal into a voice section and a non-voice section; removing a noise in the voice section of the voice signal using noise information in the non-voice section of the voice signal; and extracting a feature vector from the voice signal noise-removed by the noise removing unit and detecting a keyword from the voice section of the voice signal using the feature vector.

Claims

1. An embedded auditory system, comprising:

a voice detecting unit for receiving a voice signal as an input and dividing the voice signal into a voice section and a non-voice section;

a noise removing unit for removing a noise in the voice section of the voice signal using noise information in the non-voice section of the voice signal; and

a keyword spotting unit for extracting a feature vector from the voice signal noise-removed by the noise removing unit and detecting a keyword from the voice section of the voice signal using the feature vector.

2. The embedded auditory system according to claim 1, further comprising a sound source localizing unit for performing the localization of the voice signal in the voice section divided by the voice detecting unit.

3. The embedded auditory system according to claim 1, wherein, when performing fast Fourier transform (FFT) for transforming a voice signal from a time domain to a frequency domain, a plurality of first FFT results are obtained by dividing the voice signal into a plurality of sections and performing the FFT with respect to the divided sections, and a second FFT result is obtained by adding up the plurality of first FFT results.

4. The embedded auditory system according to claim 1, wherein the noise removing unit is a multichannel Wiener filter.

5. The embedded auditory system according to claim 4, wherein the multichannel Wiener filter uses a mel-frequency and removes a noise using a mel-frequency standard sharing technique in which filter coefficients are estimated at some frequencies, and the estimation result of filter coefficients at adjacent frequencies is shared at frequencies that are not estimated.

6. A method for processing a voice signal, the method comprising:

receiving a voice signal as an input and dividing the voice signal into a voice section and a non-voice section;

removing a noise in the voice section of the voice signal using noise information in the non-voice section of the voice signal; and

extracting a feature vector from the voice signal noise-removed by the noise removing unit and detecting a keyword from the voice section of the voice signal using the feature vector.

7. The method according to claim 6, further comprising performing the localization of the voice signal in the voice section divided by the dividing of the voice signal into the voice and non-voice sections.

8. The method according to claim 6, wherein, when performing FFT for transforming a voice signal from a time domain to a frequency domain, the removing of the noise comprises:

dividing the voice signal into a plurality of sections;

performing the FFT with respect to the divided sections, thereby obtaining a plurality of first FFT results; and

adding up the plurality of first FFT results, thereby obtaining a second FFT result.

9. The method according to claim 6, wherein the removing of the noise is performed through multichannel Wiener filtering.

10. The method according to claim 9, wherein the multichannel Wiener filtering uses a mel-frequency and removes a noise using a mel-frequency standard sharing technique in which filter coefficients are estimated at some frequencies, and the estimation result of filter coefficients at adjacent frequencies is shared at frequencies that are not estimated.