Articles

There is abundance of digitised texts available in Sanskrit. However, the word segmentation task in such texts are challenging due to the issue of Sandhi. In Sandhi, words in a sentence often fuse together to form a single chunk of text, where the word delimiter vanishes and sounds at the …...

For many of the world’s languages, the Bible is the only significant bilingual, or even monolingual, text, making it a unique training re- source for tasks such as translation, named entity analysis, and transliteration. Given the Bible’s small size, however, the output of standard word alignment tools can be extremely …...

Lack of parallel training data influences the rare word problem in Neural Machine Translation (NMT) systems, particularly for under- resourced languages. Using synthetic parallel training data (data augmentation) is a promising approach to handle the rare word problem. Previously proposed methods for data augmentation do not consider language syntax when …...

Accurate prediction of suitable discourse connectives (however, furthermore, etc.) is a key component of any system aimed at building coherent and fluent discourses from shorter sentences and passages. As an example, a dialog system might assemble a long and informative answer by sampling passages extracted from different documents retrieved from …...

We present a multi-layer annotated corpus of 112 argumentative microtexts encompassing not only argument structure and discourse relations (Stede et al., 2016), but also argument schemes — the inferential relations linking premises to claims. We propose a set of guidelines for the annotation of argument schemes both for support and …...

A corpus-based study of local coherence as established by anaphoric links between the elements in the thematic (Topic) and the rhematic (Focus) parts of sentences in different genres of discourse. The study uses the Czech data present in the Prague Dependency Treebank and annotated for surface and underlying syntactic relations, …...

eRulemaking is a means for government agencies to directly reach citizens to solicit their opinions and experiences regarding newly proposed rules. The effort, however, is partly hampered by citizens’ comments that lack reasoning and evidence, which are largely ignored since government agencies are unable to evaluate the validity and strength. …...

We present an integrated representation of code-switching (CS) functions, i.e., a representation that includes various CS phenomena (intra- /inter-sentential) and modalities (written/spoken), and aims to derive CS functions from local and global properties of the code-switched discourse. By applying it to several English/Hindi CS datasets, we show that our model …...

We present multi-speaker text-to-speech corpora for Javanese and Sundanese, the second and third largest languages of Indonesia spoken by well over a hundred million people. The key objectives were to collect high-quality data in an affordable way and to share the data publicly with the speech community. To achieve this, …...

We tested the viability of partnering with local developers to create custom annotation applications and to recruit and motivate crowd contributors from their communities to perform an annotation task consisting of the assignment of toxicity ratings to Wikipedia comments. We discuss the background of the project, the design of the …...

Feeling emotion is a critical characteristic to distinguish people from machines. Among all the multi-modal resources for emotion detection, textual datasets are those containing the least additional information in addition to semantics, and hence are adopted widely for testing the developed systems. However, most of the textual emotional datasets consist …...

The presented study concentrates on the collection of emotional multimodal real-world in-car audio, video and physiological signal recordings while driving. To do so, three sensor systems were integrated in the car and four relevant emotional states of the driver were defined: neutral, positive, frustrated and anxious. To gather as natural …...

Ellipsis is an important challenge for natural language processing systems, and addressing that challenge requires large collections of relevant data. The dataset described by Anand and McCloskey (2015), consisting of 4100 occurrences, is an important step towards addressing this issue. However, many NLP technologies require much larger collections of data. …...

The Human-System Multimodal Dialogue Sharing Corpus Building Group is acting as a working group of SIG-SLUD for the purpose of constructing a corpus for evaluating elemental technologies of the multimodal dialogue system. In this paper, we report the results of recording chat dialogue data between a human and a virtual …...

SSPR (Semantics-driven Syntactic Parser for Romanian) is a neural network ensemble parser developed for Romanian (a Python 3.5 application based on the Microsoft Cognitive Toolkit 2.0 Python API) that combines the parsing decisions of a varying number (in our experiments, 3) of other parsers (MALT, RGB and MATE), using information …...

This paper presents a benchmark dataset for the task of inter-sentence relation extraction. The paper explains the distant supervision method followed for creating the dataset for inter-sentence relation extraction, involving relations previously used for standard intra- sentence relation extraction task. The study evaluates baseline models such as bag-of-words and sequence …...

In this paper, we describe a novel combination of a character-level recurrent neural-network based model and a language model applied to diacritics restoration. In many cases in the past and still at present, people often replace characters with diacritics with their ASCII counterparts. Despite the fact that the resulting text …...

In this paper, we show how distributionally-induced semantic classes can be helpful for extracting hypernyms. We present methods for inducing sense-aware semantic classes using distributional semantics and using these induced semantic classes for filtering noisy hypernymy relations. Denoising of hypernyms is performed by labeling each semantic class with its hypernyms. …...

Automatically scoring metaphor novelty is an unexplored topic in natural language processing, and research in this area could benefit a wide range of NLP tasks. However, no publicly available metaphor novelty datasets currently exist, making it difficult to perform research on this topic. We introduce a large corpus of metaphor …...

Knowledge Base Population (KBP) is an evaluation series within the Text Analysis Conference (TAC) evaluation campaign conducted by the National Institute of Standards and Technology (NIST). Over the past nine years TAC KBP evaluations have targeted information extraction technologies for the population of knowledge bases comprised of entities, relations, and …...