This paper describes a rather simplistic method of unsupervised morphological analysis of words in an unknown language. All what is needed is a raw text corpus in the given langua...
We present an algorithm that takes an unannotated corpus as its input, and returns a ranked list of probable morphologically related pairs as its output. The algorithm tries to di...
Abstract. While classical approaches to unsupervised morphology acquisition often rely on metrics based on information theory for identifying morphemes, we describe a novel approac...
We describe an entirely statistics-based, unsupervised, and languageindependent approach to multilingual information retrieval, which we call Latent Morpho-Semantic Analysis (LMSA...
Multilingual parallel text corpora provide a powerful means for propagating linguistic knowledge across languages. We present a model which jointly learns linguistic structure for...