Morphological Features

We present an approach to using a mor- phological analyzer for tokenizing and morphologically tagging (including part- of-speech tagging) Arabic words in one process. We learn classifiers for individual morphological …...

This paper presents a corrective model for speech recognition of inflected lan- guages. The model, based on a discrim- inative framework, incorporates word n- grams features as well as factored …...

In this paper, we present a rule based model for morphological disambiguation of Turkish. The rules are generated by a novel decision list learning algorithm us- ing supervised training. Morphological …...

We present a two-stage multilingual de- pendency parser and evaluate it on 13 diverse languages. The first stage is based on the unlabeled dependency pars- ing models described by McDonald …...

We present a method for Noun Phrase chunking in Hebrew. We show that the traditional definition of base-NPs as non- recursive noun phrases does not apply in Hebrew, and propose …...

We present the first results on parsing the SYNTAGRUS treebank of Russian with a data-driven dependency parser, achieving a labeled attachment score of over 82% and an unlabeled attachment score …...

English pronouns like he and they reliably re- flect the gender and number of the entities to which they refer. Pronoun resolution systems can use this fact to filter noun …...

We explore the contribution of morphologi- cal features – both lexical and inflectional – to dependency parsing of Arabic, a morpho- logically rich language. Using controlled ex- periments, we find …...

We investigate a language model that com- bines morphological and shape features with a Kneser-Ney model and test it in a large crosslingual study of European languages. Even though the …...

We compare three methods of modeling morphological features in statistical ma- chine translation (SMT) from English to Arabic, a morphologically rich language. Features can be modeled as part of the …...

AbstractJoint morphological and syntactic analysis has been proposed as a way of improving parsing accuracy for richly inflected languages. Starting from a transition-based model for joint part-of-speech tagging and dependency …...

This paper describes a temporal expression identification and normalization system, Man- TIME, developed for the TempEval-3 chal- lenge. The identification phase combines the use of conditional random fields along with …...

Translating from English, a morphologi- cally poor language, into morphologically rich languages such as Persian comes with many challenges. In this paper, we present an approach to rich morphology predic- …...

This paper describes the system submit- ted for the Sentiment Analysis in Twitter Task of SEMEVAL 2014 and specifically the Message Polarity Classification sub- task. We used a 2–stage pipeline …...

Definiteness expresses a constellation of semantic, pragmatic, and discourse properties—the communicative functions—of an NP. We present a supervised classifier for English NPs that uses lexical, morphological, and syntactic features to …...

AbstractRecent developments in computer technology have allowed the construction and widespread application of large-scale speech corpora. To foster ease of data retrieval for people interested in utilising these speech corpora, …...

In the context of Social Media Analytics, Natural Language Processing tools face new chal- lenges on on-line conversational text, such as microblogs, chat, or text messages, because of the specificity …...

We propose a novel pipeline for translation into morphologically rich languages which consists of two steps: initially, the source string is enriched with target morphological features and then fed into …...

Neural machine translation has recently achieved impressive results, while using little in the way of external linguistic in- formation. In this paper we show that the strong learning capability of …...

AbstractIn this paper, we first build a manually annotated named entity corpus of Mongolian. Then, we propose three morphological processing methods and study comprehensive features, including syllable features, lexical features, …...

AbstractWhile measuring the readability of texts has been a long-standing research topic, assessing the technicality of terms has only been addressed more recently and mostly for the English language. In …...

AbstractRecognizing and distinguishing antonyms from other types of semantic relations is an essential part of language understanding systems. In this paper, we present a novel method for deriving antonym pairs …...

Discriminating between similar languages (DSL) on conversational texts is a challenging task. This paper aims at discriminating between limited-resource languages on short conversational texts, like Uyghur and Kazakh. Considering that …...

The Universal Morphology (UniMorph) project is a collaborative effort to improve how NLP handles complex morphology across the world’s languages. The project releases annotated morphological data using a universal tagset, …...

AbstractThis paper describes our system created for the SemEval-2018 Task 1: Affect in Tweets (AIT-2018). We participated in both the regression and the ordinal classification subtasks for emotion intensity detection …...

AbstractCritical to natural language generation is the production of correctly inflected text. In this paper, we isolate the task of predicting a fully inflected sentence from its partially lemmatized version. …...

AbstractWe introduce Morse, a recurrent encoder-decoder model that produces morphological analyses of each word in a sentence. The encoder turns the relevant information about the word and its context into …...

AbstractWe present that, the rank-frequency relation in textual data follows f ∝ r-𝛼(r+𝛾)-𝛽, where f is the token frequency and r is the rank by frequency, with (𝛼, 𝛽, 𝛾) …...

AbstractIn this paper, we investigate the effectiveness of using rich annotations in deep neural network (DNN)-based statistical speech synthesis. DNN-based frameworks typically use linguistic information as input features called context …...

AbstractThe written forms of Semitic languages are both highly ambiguous and morphologically rich: a word can have multiple interpretations and is one of many inflected forms of the same concept …...

AbstractThe research presented in this paper aims at enriching the manually morphosyntactically annotated part of National Corpus of Polish (NKJP1M) with a syntactic layer, i.e. dependency trees of sentences, and …...

AbstractWe evaluate two common conjectures in error analysis of NLP models: (i) Morphology is predictive of errors; and (ii) the importance of morphology increases with the morphological complexity of a …...