Summary of the paper

Title Combining Multiple Models for Speech Information Retrieval
Authors Muath Alzghool and Diana Inkpen
Abstract In this article we present a method for combining different information retrieval models in order to increase the retrieval performance in a Speech Information Retrieval task. The formulas for combining the models are tuned on training data. Then the system is evaluated on test data. The task is particularly difficult because the text collection is automatically transcribed spontaneous speech, with many recognition errors. Also, the topics are real information needs, difficult to satisfy. Information Retrieval systems are not able to obtain good results on this data set, except for the case when manual summaries are included.
Language Multiple languages
Topics Information Extraction, Information Retrieval, Speech recognition and understanding, Evaluation methodologies
Full paper Combining Multiple Models for Speech Information Retrieval
Slides Combining Multiple Models for Speech Information Retrieval
Bibtex @InProceedings{ALZGHOOL08.45,
  author = {Muath Alzghool and Diana Inkpen},
  title = {Combining Multiple Models for Speech Information Retrieval},
  booktitle = {Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)},
  year = {2008},
  month = {may},
  date = {28-30},
  address = {Marrakech, Morocco},
  editor = {Nicoletta Calzolari (Conference Chair), Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Daniel Tapias},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {2-9517408-4-0},
  note = {},
  language = {english}

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