TY - GEN
T1 - EmoBGM
T2 - 2017 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2017
AU - Konan, Cedric
AU - Suwa, Hirohiko
AU - Arakawa, Yutaka
AU - Yasumoto, Keiichi
PY - 2017/5/2
Y1 - 2017/5/2
N2 - This paper presents a study about estimating the emotions conveyed in clips of background music (BGM) to be used in an automatic slideshow creation system. The system we aimed to develop, automatically tags each given pieces of background music with the main emotion it conveys, in order to recommend the most suitable music clip to the slideshow creators, based on the main emotions of embedded photos. As a first step of our research, we developed a machine learning model to estimate the emotions conveyed in a music clip and achieved 88% classification accuracy with cross-validation technique. The second part of our work involved developing a web application using Microsoft Emotion API to determine the emotions in photos, so the system can find the best candidate music for each photo in the slideshow. 16 users rated the recommended background music for a set of photos using a 5-point likert scale and we achieved an average rate of 4.1, 3.6 and 3.0 for the photo sets 1, 2, and 3 respectively of our evaluation task.
AB - This paper presents a study about estimating the emotions conveyed in clips of background music (BGM) to be used in an automatic slideshow creation system. The system we aimed to develop, automatically tags each given pieces of background music with the main emotion it conveys, in order to recommend the most suitable music clip to the slideshow creators, based on the main emotions of embedded photos. As a first step of our research, we developed a machine learning model to estimate the emotions conveyed in a music clip and achieved 88% classification accuracy with cross-validation technique. The second part of our work involved developing a web application using Microsoft Emotion API to determine the emotions in photos, so the system can find the best candidate music for each photo in the slideshow. 16 users rated the recommended background music for a set of photos using a 5-point likert scale and we achieved an average rate of 4.1, 3.6 and 3.0 for the photo sets 1, 2, and 3 respectively of our evaluation task.
UR - http://www.scopus.com/inward/record.url?scp=85020117540&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85020117540&partnerID=8YFLogxK
U2 - 10.1109/PERCOMW.2017.7917587
DO - 10.1109/PERCOMW.2017.7917587
M3 - Conference contribution
AN - SCOPUS:85020117540
T3 - 2017 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2017
SP - 351
EP - 356
BT - 2017 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2017
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 12 March 2017 through 16 March 2017
ER -