AudioPairBank: towards a Large-Scale Tag-Pair-based Audio Content Analysis
Journal
EURASIP Journal on Audio, Speech, and Music Processing
Type
journal article
Date Issued
2018-09-15
Author(s)
Research Team
AIML Lab
Abstract
Recently, sound recognition has been used to identify sounds, such as the sound of a car, or a river. However, sounds have nuances that may be better described by adjective-noun pairs such as “slow car” and verb-noun pairs such as “flying insects,” which are underexplored. Therefore, this work investigates the relationship between audio content and both adjective-noun pairs and verb-noun pairs. Due to the lack of datasets with these kinds of annotations, we collected and processed the AudioPairBank corpus consisting of a combined total of 1123 pairs and over 33,000 audio files. In this paper, we include previously unavailable documentation of the challenges and implications of collecting audio recordings with these types of labels. We have also shown the degree of correlation between the audio content and the labels through classification experiments, which yielded 70% accuracy. The results and study in this paper encourage further exploration of the nuances in sounds and are meant to complement similar research performed on images and text in multimedia analysis.
Language
English
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher
Springer
Volume
2018
Number
12
Pages
12
Subject(s)
Division(s)
Eprints ID
258201
File(s)![Thumbnail Image]()
open.access
Name
s13636-018-0137-5.pdf
Size
1.4 MB
Format
Adobe PDF
Checksum (MD5)
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