%Aigaion2 BibTeX export from Idiap Publications
%Tuesday 03 December 2024 06:24:17 PM

@INCOLLECTION{kurimo-wsom99b,
         author = {Kurimo, Mikko},
         editor = {Oja, Erkki and Kaski, Samuel},
       projects = {Idiap},
          title = {Indexing Audio Documents by using Latent Semantic Analysis and SOM},
      booktitle = {Kohonen Maps},
           year = {1999},
      publisher = {Elsevier},
           note = {IDIAP-RR 99-13},
       crossref = {kurimo-wsom99},
       abstract = {This paper describes an important application for state-of-art automatic speech recognition, natural language processing and information retrieval systems. Methods for enhancing the indexing of spoken documents by using latent semantic analysis and self-organizing maps are presented, motivated and tested. The idea is to extract extra information from the structure of the document collection and use it for more accurate indexing by generating new index terms and stochastic index weights. Indexing methods are evaluated for two broadcast news databases (one French and one English) using the average document perplexity defined in this paper and test queries analyzed by human experts},
            pdf = {https://publications.idiap.ch/attachments/papers/1999/wsom99.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/papers/speech/kurimo-wsom99.ps.gz},
ipdmembership={speech},
}



crossreferenced publications: 
@TECHREPORT{kurimo-wsom99,
         author = {Kurimo, Mikko},
       projects = {Idiap},
          title = {Indexing Audio Documents by using Latent Semantic Analysis and SOM},
           type = {Idiap-RR},
         number = {Idiap-RR-13-1999},
           year = {1999},
    institution = {IDIAP},
           note = {Published in ``Kohonen Maps'', Elsevier, 1999},
       abstract = {This paper describes an important application for state-of-art automatic speech recognition, natural language processing and information retrieval systems. Methods for enhancing the indexing of spoken documents by using latent semantic analysis and self-organizing maps are presented, motivated and tested. The idea is to extract extra information from the structure of the document collection and use it for more accurate indexing by generating new index terms and stochastic index weights. Indexing methods are evaluated for two broadcast news databases (one French and one English) using the average document perplexity defined in this paper and test queries analyzed by human experts},
            pdf = {https://publications.idiap.ch/attachments/reports/1999/rr99-13.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/1999/rr99-13.ps.gz},
ipdmembership={speech},
}