CHAPTER kurimo-wsom99b/IDIAP Indexing Audio Documents by using Latent Semantic Analysis and SOM Kurimo, Mikko Oja, Erkki Ed. Kaski, Samuel Ed. EXTERNAL https://publications.idiap.ch/attachments/papers/1999/wsom99.pdf PUBLIC https://publications.idiap.ch/index.php/publications/showcite/kurimo-wsom99 Related documents Kohonen Maps 1999 Elsevier 363-374 IDIAP-RR 99-13 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 REPORT kurimo-wsom99/IDIAP Indexing Audio Documents by using Latent Semantic Analysis and SOM Kurimo, Mikko EXTERNAL https://publications.idiap.ch/attachments/reports/1999/rr99-13.pdf PUBLIC Idiap-RR-13-1999 1999 IDIAP Published in ``Kohonen Maps'', Elsevier, 1999 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