Method for separating monaural overlapping speeches based on fractional Fourier transform (FrFT)

A technology of fractional Fourier and speech separation, applied in speech analysis, instruments, etc., can solve problems such as separation, achieve effective separation and reduce extension

Inactive Publication Date: 2011-05-11
BEIJING INSTITUTE OF TECHNOLOGYGY
View PDF0 Cites 31 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0009] The purpose of the present invention is to overcome the defective of prior art, solve the problem how to separate target speech from monophonic aliasing speech signal, propose a kind of new monophonic aliasing speech separation method based on fractional order Fourier transform

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 for separating monaural overlapping speeches based on fractional Fourier transform (FrFT)
  • Method for separating monaural overlapping speeches based on fractional Fourier transform (FrFT)
  • Method for separating monaural overlapping speeches based on fractional Fourier transform (FrFT)

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0027] Preferred embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0028] A monophonic aliasing speech separation method based on fractional Fourier transform, the implementation process is as follows figure 1 shown, including the following steps:

[0029] Step 1: Perform preprocessing on the aliased speech signal, remove the silent segment signal, and find out the voiced sound frame.

[0030] First, endpoint detection is performed on the aliased speech signal, the silent segment signal is removed, and the remaining aliased segment signal is taken as the processing object. Endpoint detection can use the combination of short-term energy and zero-crossing rate.

[0031] Then, the remaining aliasing section signals are divided into frames, the frame length is 20ms, and the frame shift is 10ms. At this time, unvoiced and voiced sound is judged, and the voiced sound frame is marked. The unvoiced and voiced judg...

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 method for separating monaural overlapping speeches based on fractional Fourier transform (FrFT), which belongs to the technical field of audio signal processing. The method comprises the following steps: firstly, preprocessing overlapping speech signals so as to remove mute-section signals of the overlapping speech signals and find out sonant frames; then, carrying out pitch detection on sonant-frame signals based on FrFT so as to separate the fundamental frequencies of the overlapping speeches; and finally, integrating the fundamental frequencies with a sinusoidal model of speech signals so as to synthesize speeches, thereby obtaining each speech signal subjected to separation. The method provided by the invention has the advantages that the fundamental frequencies of a plurality of overlapping speeches can be separated and extracted effectively, and finally, the effective separation of the overlapping speeches can be realized; and the pitch frequencies are extracted based on FrFT instead of traditional fast Fourier transform (FFT), thereby reducing the extension of a harmonic frequency spectrum and then obtaining more accurate fundamental frequencies of original signals. The method provided by the invention is especially suitable for the separation of monaural overlapping speeches containing speeches of two persons.

Description

technical field [0001] The invention relates to a method for separating monophonic aliasing speech by using fractional Fourier transform, and belongs to the technical field of audio signal processing. Background technique [0002] In the field of speech and auditory signal processing, an important problem is how to separate the speech of interest from the aliased speech signal. Aliasing speech separation has important theoretical significance and practical value in speech communication, acoustic target detection, sound signal enhancement, etc. It is difficult for speech enhancement methods to separate the speech that people are interested in (called the target speech) from the interference speech. [0003] Fractional Fourier Transform (FrFT) has excellent characteristics for analyzing some non-stationary signals, and has become a tool that has attracted widespread attention in the signal processing field in recent years. Speech as a non-stationary signal, the application o...

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 Applications(China)
IPC IPC(8): G10L11/00G10L25/78
Inventor 茹婷婷谢湘匡镜明
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

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