International audienceThis paper discusses the adaptation of vocabularies for automatic speech recognition. The context is the transcriptions of videos in French, English and Arabic. Baseline automatic speech recognition systems have been developed using available data. However, the available text data, including the GigaWord corpora from LDC, are getting quite old with respect to recent videos that are to be transcribed. The paper presents the collection of recent textual data from internet for updating the speech recognition vocabularies and training the language models, as well as the elaboration of development data sets necessary for the vocabulary selection process. The paper also compares the coverage of the training data collected fr...
One of the most prevailing problems of large-vocabulary speech recognition systems is the large numb...
A way to improve outputs produced by automatic speech recognition (ASR) systems is to integrate addi...
Dans cette thèse, nous proposons un processus d'adaptation thématique non supervisée qui vise à spéc...
International audienceThis paper discusses the adaptation of speech recognition vocabularies for aut...
Current automatic speech recognition (ASR) systems are based on language models (LM) which gather wo...
Modern automatic speech recognition (ASR) systems are speaker independent and designed to recognize ...
A regular automatic speech recognizer works with a so-called recognition lexicon. This lexicon conta...
International audienceOut-of-vocabulary (OOV) words can pose a particular problem for automatic spee...
Language models used in current automatic speech recognition systems are trained on general-purpose ...
Adapting the vocabulary of a speech recognizer to the utterance to be recognized has proven to be su...
Transcription of multimedia data sources is often a challenging automatic speech recognition (ASR) t...
International audienceProper name recognition is a challenging task in information retrieval from la...
With the development of technologies operating in a multilingual context, portability of speech tech...
International audienceThis paper presents CLIPS laboratory activities in speech recognition related ...
The diachronic nature of broadcast news causes frequent variations in the linguisticcontent and voca...
One of the most prevailing problems of large-vocabulary speech recognition systems is the large numb...
A way to improve outputs produced by automatic speech recognition (ASR) systems is to integrate addi...
Dans cette thèse, nous proposons un processus d'adaptation thématique non supervisée qui vise à spéc...
International audienceThis paper discusses the adaptation of speech recognition vocabularies for aut...
Current automatic speech recognition (ASR) systems are based on language models (LM) which gather wo...
Modern automatic speech recognition (ASR) systems are speaker independent and designed to recognize ...
A regular automatic speech recognizer works with a so-called recognition lexicon. This lexicon conta...
International audienceOut-of-vocabulary (OOV) words can pose a particular problem for automatic spee...
Language models used in current automatic speech recognition systems are trained on general-purpose ...
Adapting the vocabulary of a speech recognizer to the utterance to be recognized has proven to be su...
Transcription of multimedia data sources is often a challenging automatic speech recognition (ASR) t...
International audienceProper name recognition is a challenging task in information retrieval from la...
With the development of technologies operating in a multilingual context, portability of speech tech...
International audienceThis paper presents CLIPS laboratory activities in speech recognition related ...
The diachronic nature of broadcast news causes frequent variations in the linguisticcontent and voca...
One of the most prevailing problems of large-vocabulary speech recognition systems is the large numb...
A way to improve outputs produced by automatic speech recognition (ASR) systems is to integrate addi...
Dans cette thèse, nous proposons un processus d'adaptation thématique non supervisée qui vise à spéc...