An HMM Based System for Acoustic Event Detection

Authors:
Christian Zieger
Affiliations:
FBK-irst, Povo, Italy 38050
Venue:
Multimodal Technologies for Perception of Humans
Year:
2008

Citing 4
Cited 1

Fundamentals of speech recognition

Fundamentals of speech recognition
Audio events detection based highlights extraction from baseball, golf and soccer games in a unified framework

ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 3 (ICME '03) - Volume 03
Computational Auditory Scene Analysis: Principles, Algorithms, and Applications

Computational Auditory Scene Analysis: Principles, Algorithms, and Applications
CLEAR evaluation of acoustic event detection and classification systems

CLEAR'06 Proceedings of the 1st international evaluation conference on Classification of events, activities and relationships

A Person Tracking System for CHIL Meetings

Multimodal Technologies for Perception of Humans

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper deals with the CLEAR 2007 evaluation on the detection of acoustic events which happen during seminars. The proposed system first converts an audio sequence in a stream of MFCC features, then a detecting/classifying block identifies an acoustic event with time stamps and assign to it a label among all possible event labels. Identification and classification are based on Hidden Markov Models (HMM). The results, measured in terms of two metrics (accuracy and error rate) are obtained applying the implemented system on the interactive seminars collected under the CHIL project. Final not very good results highlight the task complexity.