This article surveys work on Unsupervised Learning of Morphology. We define
Unsupervised Learning of Morphology as the problem of inducing a description (of some …

State-of-the-art large vocabulary continuous speech recognition systems use mostly phone
based acoustic models (AMs) and word based lexical and language models. However …

gram models are the most widely used language models in large vocabulary continuous
speech recognition. Since the size of the model grows rapidly with respect to the model …

This paper describes a novel recognition driven segmentation methodology for Devanagari
Optical Character Recognition. Prior approaches have used sequential rules to segment …

This paper aims to make up for the lack of documented baselines for Hungarian language
modeling. Various approaches are evaluated on three publicly available Hungarian corpora …

ABSTRACT Out-of-vocabulary (OOV) words are a major source of error in a speech
recognition system and various methods have been proposed to increase the performance …

This paper describes a morpheme-based pronunciation model that is especially useful to
develop the pronunciation lexicon for Large Vocabulary Continuous Speech Recognition …

This thesis demonstrates that machine learning can be applied in different ways to automate
the analysis of morphologically complex agglutinating languages. Firstly, the target …

This paper presents the application of morpheme-based and factored language models in
an Amharic speech recognition task. Since the use of morphemes in both acoustic and …