Mandarin Chinese has two strategies for forming comparatives of superiority: one in which the standard of comparison is introduced by the morpheme bi, and one that resembles a transitive verb construction, in which the standard of comparison directly follows a gradable adjective. The ‘transitive comparative’ exhibits two special restrictions: the predicate must be one that accepts differential ...

We propose a language-independent approach for improving statistical machine translation for morphologically rich languages using a hybrid morpheme-word representation where the basic unit of translation is the morpheme, but word boundaries are respected at all stages of the translation process. Our model extends the classic phrase-based model by means of (1) word boundary-aware morpheme-level ...

This article presents the working methodology of supervised Morpheme Extraction Task for Tamil language in Morpheme Extraction Task (MET) Task of FIRE-2014. In this attempt, Tamil Morphemes are extracted based on supervised machine learning algorithm, Support vector machines.

This paper presents a morpheme-based part-of-speech tagger for Chinese. It consists of two main components, namely a morpheme segmenter to segment each word in a sentence into a sequence of morphemes, based on forward maximum matching, and a lexical tagger to label each morpheme with a proper tag indicating its position pattern in forming a word of a specific class, based on lexicalized hidden ...

This paper presents our segmentation system developed for the MLP 2017 shared tasks on cross-lingual word segmentation and morpheme segmentation. We model both word and morpheme segmentation as character-level sequence labelling tasks. The prevalent bidirectional recurrent neural network with conditional random fields as the output interface is adapted as the baseline system, which is further i...

This paper extends the training and tuning regime for phrase-based statistical machine translation to obtain fluent translations into morphologically complex languages (we build an English to Finnish translation system). Our methods use unsupervised morphology induction. Unlike previous work we focus on morphologically productive phrase pairs – our decoder can combine morphemes across phrase bo...

Both dictionary-based and rule-based methods on grapheme-to-phoneme conversion have their own advantages and limitations. For example, a large sized phonetic dictionary and complex morphophonemic rules are required for the dictionary-based method and the LTS(letter to sound) rule-based method itself cannot model the complete morphophonemic constraints. This paper describes a grapheme-to-phoneme...

Most of errors in Korean morphological analysis and POS (Part-of-Speech) tagging are caused by unknown morphemes. This paper presents a generalized unknown morpheme handling method with P OSTAG (POStech TAGger) which is a statistical/rule based hybrid POS tagging system. The generalized unknown morpheme guessing is based on a combination of a morpheme pattern dictionary which encodes general le...

Reading and understanding morphologically complex words can sometimes be a particular challenge to nonnative speakers. For example, compound words consist of multiple free morphemes, oftentimes without explicit marking of the morpheme boundaries. In a lexical decision task, we investigated compound reading in native and nonnative speakers of Dutch. The compounds differed in that the letter bigr...