REAL-TIME SPEAKER-ADAPTIVE SPEECH RECOGNITION APPARATUS AND METHOD

• US 20110066426A1
• Filed: 07/15/2010
• Published: 03/17/2011
• Est. Priority Date: 09/11/2009
• Status: Abandoned Application

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Samsung Electronics Co. Ltd.
• Inventors: LEE, Gil Ho
• Application Number:
  US12/836,971
• Publication Number:
  US 20110066426A1
• Time in Patent Office: Days
• US Class Current: 704/207
• CPC Class Codes: G10L 15/02 Feature extraction for speech recognition; Selection of recognition unit
• CPC Class Codes: G10L 15/07 to the speaker
• CPC Class Codes: G10L 25/90 Pitch determination of speech signals

Abstract

A speech recognition apparatus and method for real-time speaker adaptation are provided. The speech recognition apparatus may estimate a pitch of a speech section from an inputted speech signal, extract a speech feature for speech recognition based on the estimated pitch, and perform speech recognition with respect to the speech signal based on the speech feature. The speech recognition apparatus may be adaptively normalized depending on a speaker. Thus, the speech recognition apparatus may extract a speech feature for speech recognition, and may improve a performance of speech recognition based on the extracted speech feature.

Claims

1. A speech recognition apparatus, comprising:

a pitch estimation unit configured to extract a speech section from a speech signal and to estimate a pitch of the speech section;

a speech feature extraction unit configured to extract a speech feature for speech recognition from the speech section based on the estimated pitch; and

a speech recognition unit configured to perform speech recognition with respect to the speech signal based on the extracted speech feature.

2. The speech recognition apparatus of claim 1, wherein the pitch estimation unit comprises:

a speech section extraction unit configured to extract the speech section, the speech section comprising a starting point and an ending point of the speech section; and

a voice determination unit configured to determine whether the speech section is a voice frame or an unvoiced frame.

3. The speech recognition apparatus of claim 2, wherein the pitch estimation unit is further configured to:

estimate the pitch of the speech section when the speech section is the voice frame; and

replace the pitch of the speech section with a pitch of one or more previous voice frames when the speech section is an unvoiced frame.

4. The speech recognition apparatus of claim 1, wherein the speech feature extraction unit comprises:

a warping factor calculation unit configured to calculate a warping factor for vocal tract length normalization based on the estimated pitch; and

a frequency warping unit configured to perform frequency warping based on the warping factor,

wherein the speech recognition unit is further configured to perform speech recognition based on the frequency-warped speech feature.

5. The speech recognition apparatus of claim 4, wherein the speech feature extraction unit further comprises:

a preprocessing unit configured to perform pre-processing to emphasize a high frequency band of the speech signal; and

a window processing unit configured to process a Hamming window with respect to the pre-processed speech signal,

wherein the warping factor calculation unit is further configured to calculate the warping factor with respect to the speech signal where the Hamming window is processed.

6. The speech recognition apparatus of claim 4, further comprising a user feedback unit configured to perform user feedback with respect to the speech recognition.

7. The speech recognition apparatus of claim 6, wherein the warping factor calculation unit is further configured to calculate the warping factor based on the user feedback.

8. The speech recognition apparatus of claim 6, wherein the user feedback comprises information about at least one of the pitch, the warping factor, and a speech recognition rate.

9. A speech recognition method, comprising:

extracting a speech section from a speech signal and estimating a pitch of the speech section;

extracting a speech feature for speech recognition in the speech section based on the estimated pitch; and

performing speech recognition with respect to the speech signal based on the extracted speech feature.

10. The speech recognition method of claim 9, further comprising performing user feedback with respect to the speech recognition to increase an accuracy of a warping factor.

11. A voice recognition apparatus, comprising:

a pitch estimation unit configured to detect a pitch of a voice frame generated by a voice;

a voice feature extraction unit configured to extract a voice feature from the detected pitch of the voice frame; and

a voice recognition unit configured to perform voice recognition from the extracted voice feature.

12. The voice recognition apparatus of claim 11, wherein the pitch estimation unit comprises:

a voice frame extraction unit configured to extract, from the voice a starting point and an ending point of the voice frame; and

a voice determination unit configured to determine whether the speech section is a voice frame or an unvoiced frame.

13. The voice recognition apparatus of claim 11, wherein, if the voice frame is an unvoiced frame, the pitch estimation unit is further configured to replace the pitch of the unvoiced frame with a pitch of one or more previous voice frames.

14. The voice recognition apparatus of claim 11, wherein the voice feature extraction unit comprises:

a warping factor calculation unit configured to calculate a warping factor for vocal tract length normalization based on the detected pitch; and

a frequency warping unit configured to perform frequency warping based on the warping factor,

wherein the voice recognition unit is further configured to perform voice recognition based on the frequency-warped speech feature.

15. The voice recognition apparatus of claim 11, wherein the voice frame comprises at least one of:

a spoken word, a spoken sentence, and a spoken utterance.