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Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes |  |
Conference papers
Early frame-based detection of acoustic scenes
Abstract : Let us consider a specific acoustic scene appearing in a continuous audio stream recorded while making a trip a in city. In this work, we aim at detecting at the earliest opportunity the several occurrences of this scene. The objective in early detection is then to build a decision function that is able to go off as soon as possible from the onset of a scene occurrence. This implies making a decision with an incomplete information.
This paper proposes a novel framework in this area that i) can guarantee the decision made with a partial observation to be the same as the one with the full observation; ii) incorporates in a non-confusing manner the lack of knowledge about the minimal amount of information needed to make a decision. The proposed detector is based on mapping the temporal sequences to a landmarking space thanks to appropriately designed similarity functions. As a by-product, the built framework benefits from a scalable learning problem. A preliminary experimental study provides compelling results on a soundscape dataset.
Keywords :
acoustic scenes
frame-based detection
audio signal processing
acoustic signal processing
Acoustics
Reliability
Detectors
landmarking space
Early detection
event detection
scene analysis
classification
signal processing
artificial intelligence
machine learning
temporal sequences
scene occurrence
decision function
continuous audio stream
https://hal.archives-ouvertes.fr/hal-01890049
Contributor : Marie-France Robbe Connect in order to contact the contributor
Submitted on : Monday, May 9, 2022 - 4:40:42 PM
Last modification on : Wednesday, June 22, 2022 - 3:24:11 AM
Contributor : Marie-France Robbe Connect in order to contact the contributor
Submitted on : Monday, May 9, 2022 - 4:40:42 PM
Last modification on : Wednesday, June 22, 2022 - 3:24:11 AM
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