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Published on 08 September 2019

Long-Term Spectral Pseudo-Entropy (LTSPE) Feature

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kahrizi, mohammad rasoul

Description

This is the source code (MATLAB) of the LTSPE feature. Speech detection systems are known as a type of audio classifier systems which are used to recognize, detect or mark parts of audio signal including human speech. Here, a novel robust feature named Long-Term Spectral Pseudo-Entropy (LTSPE) is proposed to detect speech and its purpose is to improve performance in combination with other features, increase accuracy and to have acceptable performance. Experimental results show that if LTSPE is combined with other features, performance of the detector is improved. Moreover, this feature has higher accuracy compared to similar ones.

Citations (0)

Mentions (0)

Metrics

Dataset Index

1.2

FAIR Score

54%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

IEEE DataPort

Assigned Domain

Subfield

Aerospace Engineering

Field

Engineering

Domain

Physical Sciences

Confidence Score

51%

Source

Scholar Data Model

Keywords

Signal Processingaudio signal processingSpeech Activity Detection (SAD)voice activity detection (VAD)speech recognitionLong-Term Featurerobust featureLTSPE

Normalization Factors

FT

15.38

CTw

1.00

MTw

1.00