In this work, we describe the first public version of the Morfessor software, which is a
program that takes as input a corpus of unannotated text and produces a segmentation of …

This work presents an algorithm for the unsupervised learning, or induction, of a simple
morphology of a natural language. A probabilistic maximum a posteriori model is utilized …

We explore the use of morph-based language models in large-vocabulary continuous-
speech recognition systems across four so-called morphologically rich languages: Finnish …

In the speech recognition of highly inflecting or compounding languages, the traditional
word-based language modeling is problematic. As the number of distinct word forms can …

This paper summarizes our recent efforts for building a Turkish Broadcast News transcription
and retrieval system. The agglutinative nature of Turkish leads to a high number of out-of …

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 …

It is practically impossible to build a word-based lexicon for speech recognition in
agglutinative languages that would cover all the relevant words. The problem is that words …

Speech technology offers great promise in the field of automated literacy and reading tutors
for children. In such applications speech recognition can be used to track the reading …

This paper presents an algorithm for the unsupervised learning of a simple morphology of a
natural language from raw text. A generative probabilistic model is applied to segment word …