Speech processing for under-resourced languages is an active field of research, which has
experienced significant progress during the past decade. We propose, in this paper, a …

An automatic speech recognition (ASR) system and method are provided for using sub-
lexical language models together with word level pronunciation lexicons. These approaches …

Speech recognition systems trained for morphologically rich languages face the problem of
vocabulary growth caused by prefixes, suffixes, inflections, and compound words. Solutions …

This paper presents our work in automatic speech recognition (ASR) in the context of under-
resourced languages with application to Vietnamese. Different techniques for bootstrapping …

In this paper, a large Hungarian spoken language database is introduced. This phonetically-
based multi-purpose database contains various types of spontaneous and read speech from …

We introduce the first attempt at automatic speech recognition (ASR) in Inuktitut, as a
representative for polysynthetic, low-resource languages, like many of the 900 Indigenous …

Various morphological and acoustic modeling techniques are evaluated on a less
resourced, spontaneous Hungarian large-vocabulary continuous speech recognition …

This paper introduces two complementary language modeling approaches for
morphologically rich languages aiming to alleviate out-of-vocabulary (OOV) word problem …

In computational linguistics, language models are probabilistic models that predict the
likelihood of words occurring within specific sentences. They are key components of many …

This study investigates the possibility of using statistical machine translation to create
domain-specific language resources. We propose a methodology that aims to create a …