Detecting sound objects in audio recordings. Kumar, A., Singh, R., & Raj, B. In 2014 22nd European Signal Processing Conference (EUSIPCO), pages 905-909, Sep., 2014.
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Paper abstract bibtex
Paper abstract bibtex In this paper we explore the idea of defining sound objects and how they may be detected. We try to define sound objects and demonstrate by our experiments the existence of these objects. Most of current works on acoustic event detection focus on detecting a finite set of audio events and the detection of a generic object in sound is not done. The major reason for proposing the idea of sound objects is to work with a generic sound concept instead of working with a small set of acoustic events for detection as is the norm. Our definition tries to conform to notions present in human auditory perception. Our experimental results are promising, and show that the idea of sound objects is worth pursuing and that it could give a new direction to semi-supervised or unsupervised learning of acoustic event detection mechanisms.
@InProceedings{6952300,
author = {A. Kumar and R. Singh and B. Raj},
booktitle = {2014 22nd European Signal Processing Conference (EUSIPCO)},
title = {Detecting sound objects in audio recordings},
year = {2014},
pages = {905-909},
abstract = {In this paper we explore the idea of defining sound objects and how they may be detected. We try to define sound objects and demonstrate by our experiments the existence of these objects. Most of current works on acoustic event detection focus on detecting a finite set of audio events and the detection of a generic object in sound is not done. The major reason for proposing the idea of sound objects is to work with a generic sound concept instead of working with a small set of acoustic events for detection as is the norm. Our definition tries to conform to notions present in human auditory perception. Our experimental results are promising, and show that the idea of sound objects is worth pursuing and that it could give a new direction to semi-supervised or unsupervised learning of acoustic event detection mechanisms.},
keywords = {audio recording;detecting sound objects;audio recordings;acoustic event detection;audio events;finite set detection;generic object;generic sound concept;human auditory perception;unsupervised learning;semi-supervised learning;acoustic event detection mechanisms;Event detection;Vectors;Visualization;Detectors;Mel frequency cepstral coefficient;Computational modeling;Sound Objects;Acoustic Event Detection},
issn = {2076-1465},
month = {Sep.},
url = {https://www.eurasip.org/proceedings/eusipco/eusipco2014/html/papers/1569922657.pdf},
}Downloads: 0
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