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Latent Semantic Indexing by Self-Organizing Map

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Theme Topic Mixture Model: A Graphical Model for Document Representation

Samy Bengio, Mikaela Keller

Documents are usually represented in the bag-of-word space. However, this representation does not take into account the possible relations between words. We propose here a graphical model for representing documents: the Theme Topic Mixture Model (TTMM). Th ...

2004

Theme Topic Mixture Model: A Graphical Model for Document Representation

Samy Bengio, Mikaela Keller

IDIAP2004

Application of Information Retrieval Techniques to Single Writer Documents

Alessandro Vinciarelli

This work shows Information Retrieval experiments performed over handwritten documents produced by a single writer. The same retrieval task has been performed over both manual (no errors) and automatic (Word Error Rate around 45%) transcriptions of 200 han ...

IDIAP2004

PLSA-based Image Auto-Annotation: Constraining the Latent Space

Daniel Gatica-Perez, Florent Monay Michaud

We address the problem of unsupervised image auto-annotation with probabilistic latent space models. Unlike most previous works, which build latent space representations assuming equal relevance for the text and visual modalities, we propose a new way of m ...

2004

PLSA-based Image Auto-Annotation: Constraining the Latent Space

Daniel Gatica-Perez, Florent Monay Michaud

IDIAP2004

Information Retrieval on Noisy Text

Hervé Bourlard, David Grangier, Alessandro Vinciarelli

Spoken Document Retrieval (SDR) consists in retrieving segments of a speech database that are relevant to a query. The state-of-the-art approach to the SDR problem consists in transcribing the speech data into digital text before applying common Informatio ...

IDIAP2003

Joint Textual And Visual Cues For Retrieving Images Using Latent Semantic Indexing

Martin Vetterli, Serge Ayer, Zoran Pecenovic

In this article we present a novel approach of integrating textual and visual descriptors of images in a uniﬁed retrieval structure. The methodology, inspired from text retrieval and information ﬁltering is based on Latent Semantic Indexing (LS1). ...

2001

Thematic Indexing of Spoken Documents by Using Self-Organizing Maps

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 ...

IDIAP2000

Fast latent semantic indexing of spoken documents by using self-organizing maps

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 ...

2000

Indexing spoken audio by LSA and SOMs

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 ...

IDIAP2000