Special audio event layered and generalized identification method based on SVM (Support Vector Machine) and GMM (Gaussian Mixture Model)

A recognition method and audio technology, applied in character and pattern recognition, computer parts, instruments, etc., can solve the problems of high missed detection rate of audio event clips, low audio event recognition accuracy, slow audio event recognition speed, etc. The effect of reducing interference, improving computing performance and recognition efficiency

Inactive Publication Date: 2012-11-28
BEIJING INSTITUTE OF TECHNOLOGYGY
View PDF3 Cites 69 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0019] The purpose of the present invention is to solve the problems of low audio event recognition accuracy, short-duration audio event segment missing detection rate, and slow audio event recognition speed in continuous audio event streams, and propose a specific audio event that com

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
  • Special audio event layered and generalized identification method based on SVM (Support Vector Machine) and GMM (Gaussian Mixture Model)
  • Special audio event layered and generalized identification method based on SVM (Support Vector Machine) and GMM (Gaussian Mixture Model)
  • Special audio event layered and generalized identification method based on SVM (Support Vector Machine) and GMM (Gaussian Mixture Model)

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0072] In order to better illustrate the purpose, technical solutions and advantages of the present invention, the method of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0073] The invention is a model-based specific audio event detection method. The method first preprocesses each original audio signal, extracts audio feature parameters MFCC, and trains by inputting training audio feature files into GMM and SVM respectively to generate The GMM model and SVM classifier finally implement a specific audio event layered recognition method that combines GMM and SVM. This method can quickly and accurately identify specific audio events in the audio event stream, and output the start and end time of the audio event. The principle of the layered recognition method for specific audio events fused with GMM and SVM proposed in the present invention is as follows: figure 1 shown.

[0074] Technical scheme...

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 relates to a special audio event layered and generalized identification method based on a combination of an SVM (Support Vector Machine) and a GMM (Gaussian Mixture Model), and belongs to the technical field of a computer and audio event identification. The special audio event layered and generalized identification method comprises the following steps of: firstly, obtaining an audio characteristic vector file of a training sample; secondly, respectively carrying out model training on a great quantity of audio characteristic vector files (of the training samples) with various types by using a GMM method and an SVM method, so as to obtain the GMM model with generalization capability and an SVM classifier, and complete offline training; and finally, carrying out layered identification on the audio characteristic vector files to be identified by using the GMM model and the SVM classifier. With the adoption of the method provided by the invention, the problems that the conventional special audio event identification is low in identification efficiency on a continuous audio stream, very short in continuing time, high in audio event false dismissal probability can be solved. The method can be applied to searching a special audio and monitoring a network audio based on contents.

Description

technical field [0001] The invention relates to a layered and generalized recognition method for a specific audio event that combines a support vector machine (SVM) and a Gaussian mixture model (GMM), and belongs to the technical field of computer and audio event recognition. Background technique [0002] A specific audio event is an audio segment designated by the user with a specific semantic or content. [0003] With the rapid development of computer and network technology, the rapid expansion of audio and video files and streaming media data, it is becoming more and more important to quickly and accurately find or identify the required specific audio events from the massive audio information. Due to the urgent needs of applications such as traffic monitoring and security monitoring in sensitive areas, specific audio event recognition technology has been extensively studied in recent years. [0004] Specific audio event recognition technology is to identify specific audi...

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): G06K9/62
Inventor 罗森林王坤潘丽敏谢尔曼
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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