Title
AudioPairBank: towards a large-scale tag-pair-based audio content analysis
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.
Year
DOI
Venue
2018
10.1186/s13636-018-0137-5
EURASIP Journal on Audio, Speech, and Music Processing
Keywords
Field
DocType
Sound event database,Audio content analysis,Machine learning,Signal processing
Sound recognition,Audio content analysis,Computer science,Speech recognition,Documentation
Journal
Volume
Issue
ISSN
2018
1
1687-4722
Citations 
PageRank 
References 
2
0.38
18
Authors
6
Name
Order
Citations
PageRank
Sebastian Säger120.38
Benjamin Elizalde235922.38
Damian Borth376449.45
Christian Schulze420.38
Raj, Bhiksha52094204.63
Ian R. Lane625933.64