Method and device for noise suppression, phonetic feature extraction, speech recognition and training voice model

A technology for noise suppression and speech features, which is applied in the field of noise suppression of speech spectrum, and can solve the problem of a large amount of calculation of the gain function.

Inactive Publication Date: 2008-04-02
KK TOSHIBA
View PDF0 Cites 14 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] 2. Using Taylor series accumulation or numerical integration to calculate the gain function requires a lot of calculation

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method and device for noise suppression, phonetic feature extraction, speech recognition and training voice model
  • Method and device for noise suppression, phonetic feature extraction, speech recognition and training voice model
  • Method and device for noise suppression, phonetic feature extraction, speech recognition and training voice model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0034] In order to facilitate the understanding of the following embodiments, the principles of minimum mean square error (MMSE) estimation and log spectrum minimum mean square error (LogMMSE) estimation are briefly introduced first.

[0035] MMSE estimation is a speech enhancement algorithm, which uses the estimated spectrum of background noise to suppress the noise in the noisy speech spectrum to obtain the speech spectrum with noise suppressed. Specifically, the minimum mean square error estimation is performed by the following formula:

[0036] y(t)=x(t)+d(t), 0≤t≤T (1)

[0037] A ^ k = E { A k | y ( t ) , 0 ≤ t ≤ T } - - - ( 2 )

...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides a noise reduction method, a method for extracting phonetic feature, a speech recognition method and a speech model training method as well as a noise reduction device, a device for extracting phonetic feature, a speech recognition device and a speech model training device. According to one aspect of the invention, the noise reduction method which is used in speech spectrum containing noise includes the following steps: according to a noise estimation spectrum, logarithm spectrum minimum mean square error estimation of the speech spectrum is completed to reduce the noise contained in the speech spectrum, wherein, the logarithm spectrum minimum mean square error estimation is realized through calculating gain function according to the following steps: the gain function is calculated through Taylor series accumulation and numerical integration; finally, the result of the Taylor series accumulation is combined with that of the numerical integration.

Description

technical field [0001] The present invention generally relates to speech recognition technology, and in particular, to noise suppression technology of speech spectrum. Background technique [0002] The current popular speech recognition system can achieve very high recognition accuracy for pure speech, but due to the mismatch between the acoustic model and the acoustic features brought about by the noise, the performance of the existing speech recognition system will drop sharply in the noisy environment. [0003] Work on noise robustness has mainly focused on front-end design to reduce noise-induced mismatches in the speech feature space. The minimum mean-square error (Minimum Mean-Square Error, MMSE) estimation is a speech enhancement algorithm, which can effectively suppress the background noise, thereby improving the signal-to-noise ratio (Signal-to-Noise Ratio, SNR) of the input signal. For the minimum mean square error estimation, in the literature "Speech enhancement...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G10L21/02G10L15/20G10L15/02G10L15/08G10L15/06G10L15/00G10L21/0216
Inventor丁沛何磊鄢翔赵蕤郝杰
OwnerKK TOSHIBA