文献类型：会议论文

英文题名：Advances in Automatic Bird Species Recognition from Environmental Audio

作者：Dong, Xueyan[1]; Jia, Jingpeng[1]

第一作者：董雪燕

通讯作者：Dong, Xueyan

机构：[1] Special Education College, Beijing Union University, Beijing, 100070, China

第一机构：北京联合大学特殊教育学院

会议论文集：2020 5th International Conference on Intelligent Computing and Signal Processing, ICSP 2020

会议日期：March 20, 2020 - March 22, 2020

会议地点：Suzhou, China

语种：英文

外文关键词：Feature extraction - Image processing - Intelligent computing - Remote sensing

摘要：Bioacoustics has recently become one of the "big data" research topics since many bird monitoring projects have collected terabytes of audio using remote sensors. The challenge in recent years is to develop algorithms to realize fully automatic recognition of bird species through analysing environmental recordings. A number of approaches directly draw on experience of effective algorithms in signal processing and image processing areas. They seem working well for small data or lab data, however, the outcomes for large-scale environmental data shows a big gap between theoretical experiments and real applications. To provide possible clues for future research, we review the state-of-art development in automated bird species recognition, and identify wide range of algorithms on noise removal, bird call detection, feature extraction for classification. The significant software tools and publicly available datasets for the task are presented. This survey can be valuable for new researchers who are about to start the journey with birdsong analysis. ? 2019 Published under licence by IOP Publishing Ltd.