Abstract Out-of-vocabulary (OOV) words are unknown words that appear in the testing
speech but not in the recognition vocabulary. They are usually important content words such …

The paper addresses the issue of confidence measure reliability provided by automatic
speech recognition systems for use in various spoken language processing applications. In …

In this paper, we address a relatively new task: prediction of ASR performance on unseen
broadcast programs. We first propose an heterogenous French corpus dedicated to this task …

We present a novel approach for improving communication success between users of
speech-to-speech translation systems by automatically detecting errors in the output of …

Ensuring language coverage in dialog systems can be a challenge, since the language in a
domain may drift over time, creating a mismatch between the original training data and …

Recognition of Proper Names (PNs) in speech is important for content based indexing and
browsing of audio-video data. However, many PNs are Out-Of-Vocabulary (OOV) words for …

This paper addresses the problem of detecting words that are out-of-vocabulary (OOV) for a
speech recognition system to improve automatic speech translation. The detection system …

Nous abordons, dans cette thèse, une étude sur les représentations continues de mots (en
anglais word embeddings) appliquées à la détection automatique des erreurs dans les …

This paper addresses error type classification in continuous speech recognition (CSR). In
CSR, errors are classified into three types, namely, the substitution, insertion and deletion …

Word Confidence Estimation (WCE) for machine transla-tion (MT) or automatic speech
recognition (ASR) consists in judging each word in the (MT or ASR) hypothesis as correct or …