This paper proposes an indexing technique for fast retrieval of similar subsequences using the time warping distance. The time warping distance is a more suitable similarity measure than the Euclidean distance in many applications where sequences may be of different lengths and/or different sampling rates. The proposed indexing technique employs a disk-based suffix tree as an index structure an...

This article presents an unsupervised algorithm for word decomposition called UNGRADE (UNsupervised GRAph DEcomposition) to segment any word list of any language. UNGRADE assumes that each word follows the structure prefixes, a stem and suffixes without giving a limit on the number of prefixes and suffixes. The UNGRADE’s algorithm works in three steps and is language independent. Firstly, a pse...

Previous studies distinguish between right hemisphere-dominant processing of prosodic/tonal information and left-hemispheric modulation of grammatical information as well as lexical tones. Swedish word accents offer a prime testing ground to better understand this division. Although similar to lexical tones, word accents are determined by words' morphosyntactic structure, which enables listener...

Automatic indexing systems use suffix stripping algorithms to cluster various words derived from a common root under the same stem. Currently, removing affixes to either a context-free or context-sensitive operation, where the context refers to the remaining stem. In this article, we propose a suffixing algorithm which uses grammatical categories to enhance the stemming process. This approach s...

This paper presents a simple method for performing a lexical analysis of agglutinative languages like Korean, which have a heavy morphology. Especially, for nouns and adverbs with regular morphological modifications and/or high productivity, we do not need to artificially construct huge dictionaries of all inflected forms of lemmas. To construct a dictionary of lemmas and lexical transducers, f...

Morphological synthesis is an essential part of any natural language generation system. bengali is a highly inflectional language with more than 160 different inflected forms for verbs and 36 different forms for nouns, and 24 different forms for pronouns. Moreover, the choice and ordering of suffixes for nouns and structural changes in verb morphology are dependent on the type (animate/inanimat...

Word stemming is one of the most significant factors that affect the performance of a Natural Language Processing (NLP) application such as Information Retrieval (IR) system, part of speech tagging, machine translation system and syntactic parsing. Urdu language raises several challenges to NLP largely due to its rich morphology. In Urdu language, stemming process is different as compared to th...

There is a long-standing debate about the principles constraining the combinatorial properties of affixes. Hay (2002) and Hay and Plag (2004) proposed a model in which suffixes can be ordered along a hierarchy of processing complexity. We show that their model generalizes to a larger set of suffixes, and we provide independent evidence supporting their claim that a higher rank in the ordering c...

In many languages, the production of noun phrases requires the selection of gender-marked elements like determiners or inflectional suffixes. There is a recent debate as to whether the selection of freestanding gender-marked elements, such as determiners, follows the same processing mechanisms as the selection of bound gender-marked morphemes, such as adjective suffixes. Most of the evidence on...

Stemming words to (usually) remove suffixes has applications in text search, machine translation, document summarisation, and text classification. For example, English stemming reduces the words “computer”, “computing”, “computation”, and “computability” to their common morphological root, “comput-”. In text search, this permits a search for “computers” to find documents containing all words wi...