Typical approaches to the problem use short-term spectral features to describe the audio sig- nal, with additional modeling on top to take temporal context into.
This work proposes an approach to detecting and modeling acoustic events that directly describes temporal context, using convolutive non-negative matrix ...
Abstract: Automatic detection of different types of acoustic events is an interesting problem in soundtrack processing. Typical approaches to the problem ...
People also ask
What is spectral vs temporal features?
What is acoustic event detection?
Automatic detection of different types of acoustic events is an interesting problem in soundtrack processing. Typical approaches to the problem use ...
Summary: This work proposes an approach to detecting and modeling acoustic events that directly describes temporal context, using convolutive non-negative ...
It is demonstrated that the proposed spectro-temporal features achieve a better recognition accuracy than MFCCs. Index Terms— acoustic event detection, Gabor ...
In this contribution, an acoustic event detection system based on spectro-temporal features and a two-layer hidden Markov model as back-end is proposed ...
Spectro-temporal STRF and Gabor features outperform reference spectral ... acoustic event detection may yield such a compact feature set for recognition ...
Spectro-Temporal Receptive Field (STRF) is a linear function which describe the relationship between sound stimulus and pri-.
to consider signal features that capture the spectral and temporal modulations ... “Feature analysis and selection for acoustic event detection,” in ...