A Robust Feature Extraction Method Based on Log Spectral Signal-to-Noise Ratio Weighting

A technology of logarithmic spectral features and robust features, applied in the field of robust feature extraction, can solve problems such as the influence of additive noise, and achieve the effect of reducing influence, improving environmental robustness, and being easy to implement in real time.

Active Publication Date: 2019-12-10
HOHAI UNIV
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In MFCC, the smaller input value is exactly the Mel subband speech with smaller energy, and they are easily affected by additive noise

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
  • A Robust Feature Extraction Method Based on Log Spectral Signal-to-Noise Ratio Weighting
  • A Robust Feature Extraction Method Based on Log Spectral Signal-to-Noise Ratio Weighting
  • A Robust Feature Extraction Method Based on Log Spectral Signal-to-Noise Ratio Weighting

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0018] Below in conjunction with specific embodiment, further illustrate the present invention, should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various equivalent forms of the present invention All modifications fall within the scope defined by the appended claims of the present application.

[0019] Such as figure 1 As shown, the robust feature extraction method based on logarithmic spectral SNR weighting mainly includes preprocessing, short-term spectral estimation, Mel filtering, nonlinear transformation, SNR estimation, logarithmic SNR weighting, DCT and time domain difference module. The specific implementation of each module in the drawings will be described in detail below one by one.

[0020] 1. Pretreatment:

[0021] In the speech preprocessing stage, the input speech is win...

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 discloses a robustness feature extraction method based on logarithmic spectrum noise-to-signal weighting. First of all, a short-time Mel sub-band spectrum of each frame is obtained by performing acoustic preprocessing, short-time spectrum estimation and Mel filtering on input voice; then a logarithmic spectrum is obtained by performing nonlinear transformation on the Mel sub-band spectra by use of an improved logarithm function, at the same, a logarithmic spectrum domain signal-to-noise ratio of the input voice is estimated from the Mel sub-band spectra; then, a weighted logarithmic spectrum is obtained by performing weighting on the logarithmic spectrum of the input voice by use of the estimated logarithmic spectrum domain posterior signal-to-noise ratio; and finally, feature parameters of the input voice are obtained by performing discrete cosine transform and time domain differentiating on the weighted logarithmic spectrum. The method improves the environment robustness of the feature parameters extracted in a noise environment, reduces influences exerted by additive noise on a voice identification system and also has the advantages of quite small calculation amount and easy real-time realization.

Description

technical field [0001] The present invention relates to the use of an improved logarithmic function to carry out nonlinear transformation on the Mel spectrum of speech, and to weight the logarithmic spectrum after the nonlinear transformation with the logarithmic spectrum a posteriori signal-to-noise ratio to reduce the impact of noise on the speech recognition system. A stick feature extraction method belongs to the technical field of speech recognition. Background technique [0002] Due to the variability of speech signals, the recognition performance of speech recognition systems in real environments may deteriorate dramatically. Additive background noise, linear channel distortion and speaker change are the most important factors causing speech variation. Generally, the impact of speech mismatch can be reduced from three aspects: one is to extract noise-insensitive anti-noise feature parameters; the other is to estimate pure speech features from noisy speech to match th...

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
Patent Type & Authority Patents(China)
IPC IPC(8): G10L15/02G10L15/20G10L19/02G10L21/0208
CPCG10L15/02G10L15/20G10L19/0204G10L21/0208
Inventor 吕勇
Owner HOHAI UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap