Title :
A new method for OOV detection using hybrid word/fragment system
Author :
Rastrow, Ariya ; Sethy, Abhinav ; Ramabhadran, Bhuvana
Author_Institution :
Center for Language & Speech Process., Johns Hopkins Univ., Baltimore, MD
Abstract :
In this paper, we propose a new method for detecting regions with out-of-vocabulary (OOV) words in the output of a large vocabulary continuous speech recognition (LVCSR) system. The proposed method uses a hybrid system combining words and data-driven variable length sub word units. With the use of a single feature, the posterior probability of sub word units, this method outperforms existing methods published in the literature. We also presents a recipe to discriminatively train a hybrid language model to improve OOV detection rate. Results are presented on the RT04 broadcast news task.
Keywords :
speech recognition; OOV detection; discriminative training; hybrid system; large vocabulary continuous speech recognition; out-of-vocabulary words; Acoustic measurements; Acoustic signal detection; Automatic speech recognition; Error analysis; Error correction; Natural languages; Speech recognition; Statistics; Training data; Vocabulary; OOV; discriminative training; hybrid ASR system; out-of-vocabulary;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-2353-8
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2009.4960493
