The EuroMISE Center focuses on new approaches in the field of electronic health record (EHR). Among others, the structured health documentation in dentistry in the form of an EHR i...
Texts generated by automatic speech recognition (ASR) systems have some specificities, related to the idiosyncrasies of oral productions or the principles of ASR systems, that mak...
Language models used in current automatic speech recognition systems are trained on general-purpose corpora and are therefore not relevant to transcribe spoken documents dealing w...
Looking for a better understanding of spontaneous speech-related phenomena and to improve automatic speech recognition (ASR), we present here a study on the relationship between t...
Martine Adda-Decker, Claude Barras, Gilles Adda, P...
In the Autonomata project we have collected a corpus of spoken name utterances with manually corrected phonemic transcriptions of these utterances. The corpus was designed with th...
Henk van den Heuvel, Jean-Pierre Martens, Bart D'h...
Automatic processing of medical dictations poses a significant challenge. We approach the problem by introducing a statistical framework capable of identifying types and boundarie...
This paper describes the "Alborada-I3A" corpus of disordered speech, acquired during the recent years for the research in different speech technologies for the handicapp...
Oscar Saz, Eduardo Lleida, Carlos Vaquero, William...
Grounded language models represent the relationship between words and the non-linguistic context in which they are said. This paper describes how they are learned from large corpo...
We assess the current state of the art in speech summarization, by comparing a typical summarizer on two different domains: lecture data and the SWITCHBOARD corpus. Our results ca...
As performance gains in automatic speech recognition systems plateau, improvements to existing applications of speech recognition technology seem more likely to come from better u...