Speech Music Discrimination Using Class-Specific Features

Abstract

In this paper the application of the class-specific features approach to classification is demonstrated for the problem of discriminating between speech and music. Feature extraction is class-specific and can therefore be tailored to each class meaning that segment size, model orders and the type of features used can be different for the classes. The performance of the discriminator is evaluated and an example of how classification is possible without training is given.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2004
Accession Number
ADA507788

Entities

People

  • Paul Baggenstoss
  • Thomas Beierholm

Organizations

  • Naval Undersea Warfare Center

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Classification
  • Computations
  • Computer Vision
  • Discrimination
  • Feature Extraction
  • Machine Learning
  • Noise
  • Pattern Recognition
  • Power Spectra
  • Probability Density Functions
  • Random Variables
  • Recognition
  • Spectra
  • Test And Evaluation
  • Undersea Warfare

Readers

  • Regression Analysis.
  • Speech Processing/Speech Recognition.

Technology Areas

  • AI & ML