TY - JOUR
T1 - Introduction to the Special Section on Sound Scene and Event Analysis
AU - Richard, G.
AU - Virtanen, T.
AU - Bello, J. P.
AU - Ono, N.
AU - Glotin, H.
N1 - Funding Information:
Juan Pablo Bello (SM’16) received the B.Eng. in electronics from the Universidad Simón Bolívar, Venezuela, in 1998, and the Doctorate degree in electronic engineering from Queen Mary University of London, London, U.K., in 2003. He is an Associate Professor of music technology, and electrical and computer engineering, at New York University, New York, NY, USA, with a courtesy appointment at NYU’s Center for Data Science. He is the Director of the Music and Audio Research Lab (MARL), where he leads research on music and sound informatics. His research interests include digital signal processing, computer audition, and music information retrieval, topics that he teaches and in which he has published more than 80 papers and articles in books, journals, and conference proceedings. His work has been supported by public and private institutions in Venezuela, U.K., and U.S., including CAREER and Frontiers Awards from the National Science Foundation and a Fulbright scholar grant for multidisciplinary studies in France.
Publisher Copyright:
© 2014 IEEE.
PY - 2017/6
Y1 - 2017/6
N2 - The papers in this special section are devoted to the growing field of acoustic scene classification and acoustic event recognition. Machine listening systems still have difficulties to reach the ability of human listeners in the analysis of realistic acoustic scenes. If sustained research efforts have been made for decades in speech recognition, speaker identification and to a lesser extent in music information retrieval, the analysis of other types of sounds, such as environmental sounds, is the subject of growing interest from the community and is targeting an ever increasing set of audio categories. This problem appears to be particularly challenging due to the large variety of potential sound sources in the scene, which may in addition have highly different acoustic characteristics, especially in bioacoustics. Furthermore, in realistic environments, multiple sources are often present simultaneously, and in reverberant conditions.
AB - The papers in this special section are devoted to the growing field of acoustic scene classification and acoustic event recognition. Machine listening systems still have difficulties to reach the ability of human listeners in the analysis of realistic acoustic scenes. If sustained research efforts have been made for decades in speech recognition, speaker identification and to a lesser extent in music information retrieval, the analysis of other types of sounds, such as environmental sounds, is the subject of growing interest from the community and is targeting an ever increasing set of audio categories. This problem appears to be particularly challenging due to the large variety of potential sound sources in the scene, which may in addition have highly different acoustic characteristics, especially in bioacoustics. Furthermore, in realistic environments, multiple sources are often present simultaneously, and in reverberant conditions.
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U2 - 10.1109/TASLP.2017.2699334
DO - 10.1109/TASLP.2017.2699334
M3 - Review article
AN - SCOPUS:85028340233
SN - 2329-9290
VL - 25
SP - 1169
EP - 1171
JO - IEEE/ACM Transactions on Audio Speech and Language Processing
JF - IEEE/ACM Transactions on Audio Speech and Language Processing
IS - 6
ER -