Design and Implementation of Affective Android Music Player |
Michal Staszewski
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| Abstract | An affective load estimation model based on extended Affective Norms for English Words list [2] has been created. The model is used to assess emotional load (in terms of valence and arousal) of a corpus of lyrics. The ANEW [2] list has been extended with an algorithm using Latent Semantic Analysis [3] to compute term to term similarities which were then used to derive affective estimations for words not in the ANEW [2] list. Correlation between lyrics affective load and audio features is confi rmed using Pearson measure to detect statistical significance. An Android music player is subsequently developed and audio parameters and lyrics affective load are used by the algorithm implemented in this application to assign a point in valence/arousal space for selected songs. The application allows the user to change assigned valence/arousal parameters. Bayesian classi fier based model is trained to predict user preferences. An affective load estimation model based on extended Affective Norms for English Words list [1] has been created. The model is used to assess emotional load (in terms of valence and arousal) of a corpus of lyrics. The ANEW [1] list has been extended with an algorithm using Latent Semantic Analysis [2] to compute term to term similarities which were then used to derive affective estimations for words not in the ANEW [1] list. Correlation between lyrics affective load and audio features is con firmed using Pearson measure to detect statistical significance. An Android music player is subsequently developed and audio parameters and lyrics affective load are used by the algorithm implemented in this application to assign a point in valence/arousal space for selected songs. The application allows the user to change assigned valence/arousal parameters. Bayesian classi fier based model is trained to predict user preferences. |
| Type | Master's thesis [Academic thesis] |
| Year | 2012 |
| Publisher | Technical University of Denmark, DTU Informatics, E-mail: reception@imm.dtu.dk |
| Address | Asmussens Alle, Building 305, DK-2800 Kgs. Lyngby, Denmark |
| Series | IMM-M.Sc.-2012-94 |
| Note | Supervised by Associate Professor Ole Winther, owi@imm.dtu.dk, DTU Informatics |
| Electronic version(s) | [pdf] |
| Publication link | http://www.imm.dtu.dk/English.aspx |
| BibTeX data | [bibtex] |
| IMM Group(s) | Intelligent Signal Processing |