Summary of the paper

Title Co-Training for Classification of Live or Studio Music Recordings
Authors Nicolas Auguin and Pascale Fung
Abstract "The fast-spreading development of online streaming services has enabled people from all over the world to listen to music. However, it is not always straightforward for a given user to find the ""right"" song version he or she is looking for. As streaming services may be affected by the potential dissatisfaction among their customers, the quality of songs and the presence of tags (or labels) associated with songs returned to the users are very important. Thus, the need for precise and reliable metadata becomes paramount. In this work, we are particularly interested in distinguishing between live and studio versions of songs. Specifically, we tackle the problem in the case where very little-annotated training data are available, and demonstrate how an original co-training algorithm in a semi-supervised setting can alleviate the problem of data scarcity to successfully discriminate between live and studio music recordings."
Topics Information Extraction, Information Retrieval, Corpus (Creation, Annotation, etc.)
Full paper Co-Training for Classification of Live or Studio Music Recordings
Bibtex @InProceedings{AUGUIN14.1119,
  author = {Nicolas Auguin and Pascale Fung},
  title = {Co-Training for Classification of Live or Studio Music Recordings},
  booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)},
  year = {2014},
  month = {may},
  date = {26-31},
  address = {Reykjavik, Iceland},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-8-4},
  language = {english}
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