Recognizing the quality of urban sound recordings using hand-crafted and deep audio features
Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments(2019)
摘要
Soundscape can be regarded as the auditory landscape, conceived individually or at collaborative level. This paper presents a method for automatic recognition of the soundscape quality of urban recordings. Towards this end, the ATHens Urban Soundscape has been used, which is a dataset of audio recordings of ambient urban sounds, annotated in terms of the corresponding perceived soundscape quality. In order to automatically recognize the soundscape quality, both hand-crafted and deep features have been adopted. Experimental results have demonstrated that the performance of the final classifier that combines hand-crafted and deep context-aware audio features is boosted by almost 2%.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要