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The 2007 MIREX Audio Mood Classification Task: Lessons Learned
Important issues in setting up the AMC task are described, dataset construction and ground-truth labeling are analyzed, and human assessments on the audio dataset, as well as system performances from various angles are analyzed.
Multimodal Music Mood Classification Using Audio and Lyrics
- C. Laurier, Jens Grivolla, P. Herrera
- Computer ScienceSeventh International Conference on Machine…
- 11 December 2008
It is demonstrated that lyrics and audio information are complementary, and can be combined to improve a classification system, and integrating this in a multimodal system allows an improvement in the overall performance.
Music Mood Representations from Social Tags
This study demonstrates a particular relevancy of the basic emotions model with four mood clusters that can be sum-marized as: happy, sad, angry and tender.
Music Mood and Theme Classification - a Hybrid Approach
- Kerstin Bischoff, C. S. Firan, Raluca Paiu, W. Nejdl, C. Laurier, Mohamed Sordo
- Computer ScienceISMIR
This paper develops algorithms for classifying music songs by moods and themes by extending existing approaches by also considering the songs’ thematic dimensions and by using social data from the Last.fm music portal, as support for the classification tasks.
Automatic Classification of musical mood by content-based analysis
- C. Laurier
- 19 September 2011
La musica en formato digital forma parte de nuestras vidas. Automatizar la organizacion de estos datos es un gran desafio. En esta tesis, nos centramos en la clasificacion automatica de musica a…
Indexing music by mood: design and integration of an automatic content-based annotator
- C. Laurier, O. Meyers, J. Serrà, Martin Blech, P. Herrera, X. Serra
- Computer ScienceMultimedia Tools and Applications
- 1 May 2010
A user evaluation in the context of the PHAROS search engine, asking people about the utility, interest and innovation of this technology in real world use cases is reported, demonstrating the usability of this tool to annotate large-scale databases.
Annotating Music Collections: How Content-Based Similarity Helps to Propagate Labels
The main goal of the work is to ease the process of annotating huge music collections, by using content-based similarity distances as a way to propagate labels among songs.
Audio music mood classification using support vector machine
The system submitted to the MIREX Audio Music Mood Classification task is described here. It uses a set of 133 descriptors and a Support Vector Machine classifier to predict the mood cluster. The…
Exploring relationships between audio features and emotion in music
An analysis of the associations between emotion categories and audio features automatically extracted from raw audio data based on 110 excerpts from film soundtracks evaluated by 116 listeners using machine-learning techniques.
Music Mood Annotator Design and Integration
- C. Laurier, O. Meyers, J. Serrà, Martin Blech, P. Herrera
- Computer ScienceSeventh International Workshop on Content-Based…
- 3 June 2009
A robust and efficient technique for automatic music mood annotation that is robustness to different audio compression schemes, and the integration of a fast and scalable version of this technique with the European Project PHAROS is discussed.