Using vital-sensor in tracking user emotion as a contextual input for Music Recommendation System

Nguyen Thuy Le, Jin Nakazawa, Kazunori Takashio, Hideyuki Tokuda

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Emotion is a novel contextual key for Music Recommendation System to help users to manage their expanding digital music libraries. In this paper, we propose EmuPlayer - a Music Recommendation System (MRS) which tracks a user's emotion and suggests songs in the form of a playlist that is sorted to match the user's current emotion. For a particular emotional state of the user, the system evaluates songs according to two factors: the user's preference, and the potential of a song to influence on the user's emotional state. We evaluated both EmuPlayer Emotion Recognition accuracy and its efficiency in Recommending songs.

Original languageEnglish
Title of host publicationProceedings of the IADIS International Conference Interfaces and Human Computer Interaction 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011
Pages316-320
Number of pages5
Publication statusPublished - 2011
EventIADIS International Conference Interfaces and Human Computer Interaction 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011 - Rome, Italy
Duration: 2011 Jul 242011 Jul 26

Other

OtherIADIS International Conference Interfaces and Human Computer Interaction 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011
CountryItaly
CityRome
Period11/7/2411/7/26

Fingerprint

Recommender systems
Sensors

Keywords

  • Emotion recognition
  • Emotional model
  • Music recommendation
  • Vital-sensor

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Information Systems

Cite this

Le, N. T., Nakazawa, J., Takashio, K., & Tokuda, H. (2011). Using vital-sensor in tracking user emotion as a contextual input for Music Recommendation System. In Proceedings of the IADIS International Conference Interfaces and Human Computer Interaction 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011 (pp. 316-320)

Using vital-sensor in tracking user emotion as a contextual input for Music Recommendation System. / Le, Nguyen Thuy; Nakazawa, Jin; Takashio, Kazunori; Tokuda, Hideyuki.

Proceedings of the IADIS International Conference Interfaces and Human Computer Interaction 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011. 2011. p. 316-320.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Le, NT, Nakazawa, J, Takashio, K & Tokuda, H 2011, Using vital-sensor in tracking user emotion as a contextual input for Music Recommendation System. in Proceedings of the IADIS International Conference Interfaces and Human Computer Interaction 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011. pp. 316-320, IADIS International Conference Interfaces and Human Computer Interaction 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011, Rome, Italy, 11/7/24.
Le NT, Nakazawa J, Takashio K, Tokuda H. Using vital-sensor in tracking user emotion as a contextual input for Music Recommendation System. In Proceedings of the IADIS International Conference Interfaces and Human Computer Interaction 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011. 2011. p. 316-320
Le, Nguyen Thuy ; Nakazawa, Jin ; Takashio, Kazunori ; Tokuda, Hideyuki. / Using vital-sensor in tracking user emotion as a contextual input for Music Recommendation System. Proceedings of the IADIS International Conference Interfaces and Human Computer Interaction 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011. 2011. pp. 316-320
@inproceedings{9223e4af917749848d64764cb2791399,
title = "Using vital-sensor in tracking user emotion as a contextual input for Music Recommendation System",
abstract = "Emotion is a novel contextual key for Music Recommendation System to help users to manage their expanding digital music libraries. In this paper, we propose EmuPlayer - a Music Recommendation System (MRS) which tracks a user's emotion and suggests songs in the form of a playlist that is sorted to match the user's current emotion. For a particular emotional state of the user, the system evaluates songs according to two factors: the user's preference, and the potential of a song to influence on the user's emotional state. We evaluated both EmuPlayer Emotion Recognition accuracy and its efficiency in Recommending songs.",
keywords = "Emotion recognition, Emotional model, Music recommendation, Vital-sensor",
author = "Le, {Nguyen Thuy} and Jin Nakazawa and Kazunori Takashio and Hideyuki Tokuda",
year = "2011",
language = "English",
isbn = "9789728939526",
pages = "316--320",
booktitle = "Proceedings of the IADIS International Conference Interfaces and Human Computer Interaction 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011",

}

TY - GEN

T1 - Using vital-sensor in tracking user emotion as a contextual input for Music Recommendation System

AU - Le, Nguyen Thuy

AU - Nakazawa, Jin

AU - Takashio, Kazunori

AU - Tokuda, Hideyuki

PY - 2011

Y1 - 2011

N2 - Emotion is a novel contextual key for Music Recommendation System to help users to manage their expanding digital music libraries. In this paper, we propose EmuPlayer - a Music Recommendation System (MRS) which tracks a user's emotion and suggests songs in the form of a playlist that is sorted to match the user's current emotion. For a particular emotional state of the user, the system evaluates songs according to two factors: the user's preference, and the potential of a song to influence on the user's emotional state. We evaluated both EmuPlayer Emotion Recognition accuracy and its efficiency in Recommending songs.

AB - Emotion is a novel contextual key for Music Recommendation System to help users to manage their expanding digital music libraries. In this paper, we propose EmuPlayer - a Music Recommendation System (MRS) which tracks a user's emotion and suggests songs in the form of a playlist that is sorted to match the user's current emotion. For a particular emotional state of the user, the system evaluates songs according to two factors: the user's preference, and the potential of a song to influence on the user's emotional state. We evaluated both EmuPlayer Emotion Recognition accuracy and its efficiency in Recommending songs.

KW - Emotion recognition

KW - Emotional model

KW - Music recommendation

KW - Vital-sensor

UR - http://www.scopus.com/inward/record.url?scp=84865087654&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84865087654&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84865087654

SN - 9789728939526

SP - 316

EP - 320

BT - Proceedings of the IADIS International Conference Interfaces and Human Computer Interaction 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011

ER -