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The goal of Morpho Challenge 2009 was to evaluate unsuper-vised algorithms that provide morpheme analyses for words in different languages and in various practical applications. Morpheme analysis is particularly useful in speech recognition, information retrieval and machine translation for morphologically rich languages where the amount of different word(More)
This paper presents the evaluation of Morpho Challenge Competition 2 (information retrieval). The Competition 1 (linguistic gold standard) is described in a companion paper. In Morpho Challenge 2007, the objective was to design statistical machine learning algorithms that discover which morphemes (smallest individually meaningful units of language) words(More)
Morpho Challenge is an annual evaluation campaign for unsupervised morpheme analysis. In morpheme analysis, words are segmented into smaller meaningful units. This is an essential part in processing complex word forms in many large-scale natural language processing applications, such as speech recognition, information retrieval, and machine translation. The(More)
Pseudo-differential and Fourier series operators on the torus T n = (R/2πZ) n are analyzed by using global representations by Fourier series instead of local representations in coordinate charts. Toroidal symbols are investigated and the correspondence between toroidal and Euclidean symbols of pseudo-differential operators is established. Periodization of(More)
In this paper, we investigate methods for improving the performance of morph-based spoken document retrieval in Finnish by extracting relevant index terms from confusion networks. Our approach uses morpheme-like subword units ("morphs") for recognition and indexing. This alleviates the problem of out-of-vocabulary words, especially with inflectional(More)
Unsupervised and semi-supervised learning of morphology provide practical solutions for processing morphologically rich languages with less human labor than the traditional rule-based analyzers. Direct evaluation of the learning methods using linguistic reference analyses is important for their development, as evaluation through the final applications is(More)
Morpho Challenge is an annual evaluation campaign for unsupervised morpheme analysis. In morpheme analysis, words are segmented into smaller meaningful units. This is an essential part in processing complex word forms in many large-scale natural language processing applications, such as speech recognition, information retrieval, and machine translation. The(More)