Fast call-classification system development without in-domain training data - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2008

Fast call-classification system development without in-domain training data

Christophe Servan
Frederic Bechet

Résumé

This paper presents a new method for the fast development of call-routing systems based on pre-existing corpora and knowledge databases. This method pushes forward the reduction of specific data collection and annotation for developing a new call-classification system. No specific data collection is needed for training both for the Automatic Speech Recognition (ASR) and classification models. The main idea is to re-use existing data to train the models, according to a priori knowledge on the task targeted. The experimental framework used in this study is a call-routing system applied to a civil service information telephone application. All the a priori knowledge used to develop the system is extracted from the civil service information website as well as pre-existing corpora. The evaluation of our strategy has been made on a test corpus containing 216 utterances recorded by 10 different speakers.
Fichier principal
Vignette du fichier
FB_2008_INTERSPEECH_1.pdf (124.23 Ko) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte
Loading...

Dates et versions

hal-01158650 , version 1 (01-06-2015)

Identifiants

  • HAL Id : hal-01158650 , version 1

Citer

Christophe Servan, Frederic Bechet. Fast call-classification system development without in-domain training data. The proceedings of the International Conference on Speech and Language Processing (ICSLP) Interspeech 2008, Sep 2008, Brisbane, Australia. ⟨hal-01158650⟩

Collections

UNIV-AVIGNON LIA
71 Consultations
49 Téléchargements

Partager

Gmail Facebook X LinkedIn More