Fundamentals of speech recognition
Fundamentals of speech recognition
Classification of acoustic events using SVM-based clustering schemes
Pattern Recognition
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
Audio-based context recognition
IEEE Transactions on Audio, Speech, and Language Processing
| Hi-index | 0.00 |
This paper describes a system used in acoustic event detection task of the CLEAR 2007 evaluation. The objective of the task is to detect acoustic events (door slam, steps, paper wrapping etc.) using acoustic data from a multiple microphone set up in the meeting room environment. A system based on hidden Markov models and multi-channel audio data was implemented. Mel-Frequency Cepstral Coefficients are used to represent the power spectrum of the acoustic signal. Fully-connected three-state hidden Markov models are trained for 12 acoustic events and one-state models are trained for speech, silence, and unknown events.