N-gram-Based Low-Dimensional Representation for Document Classification
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An important problem for the information retrieval from spoken documents is how to extract those relevant documents which are poorly decoded by the speech recognizer. In this paper we propose a stochastic index for the documents based on the Latent Semanti ...
An important problem for the information retrieval from spoken documents is how to extract those relevant documents which are poorly decoded by the speech recognizer. In this paper we propose a stochastic index for the documents based on the Latent Semanti ...
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This paper presents an indexing system for spoken audio documents. The framework is indexing and retrieval of broadcast news. The proposed indexing system applies latent semantic analysis (LSA) and self-organizing maps (SOM) to map the documents into a sem ...
A method is presented to provide a useful searchable index for spoken audio documents. The task differs from the traditional (text) document indexing, because large audio databases are decoded by automatic speech recognition and decoding errors occur frequ ...
This paper describes a new latent semantic indexing (LSI) method for spoken audio documents. The framework is indexing broadcast news from radio and TV as a combination of large vocabulary continuous speech recognition (LVCSR), natural language processing ...
This paper describes a new latent semantic indexing (LSI) method for spoken audio documents. The framework is indexing broadcast news from radio and TV as a combination of large vocabulary continuous speech recognition (LVCSR), natural language processing ...
Message ordering is a fundamental abstraction in distributed systems. However, usual ordering guarantees are purely syntactic'', that is, message semantics'' is not taken into consideration, despite the fact that in several cases semantic information a ...