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We present a simple architecture for parsing transcribed speech in which an edited-word de- tector first removes such words from the sen- tence string, and then a standard statistical parser …...

We propose a new evaluation strategy for keyphrase extraction based on approximate keyphrase matching. It corresponds well with human judgments and is better suited to as- sess the performance of …...

This paper presents a conditional ran- dom field-based approach for identifying speaker-produced disfluencies (i.e. if and where they occur) in spontaneous speech transcripts. We emphasize false start re- gions, which …...

AbstractIn this paper we bring to light a novel intersection between corpus linguistics and behavioral data that can be employed as an evaluation metric for resources for low-density languages, drawing …...

. An interesting issue “whether the factual search result is better than the satisfactory one?” is discussed in this paper, and all effort is to illustrate the publicly recognized conception …...

In this paper, we extend current state-of-the- art research on unsupervised acquisition of scripts, that is, stereotypical and frequently observed sequences of events. We design, evaluate and compare different methods …...

We introduce a reinforcement learning- based approach to simultaneous ma- chine translation—producing a trans- lation while receiving input words— between languages with drastically dif- ferent word orders: from verb-final lan- …...

Word segmentation is a fundamental task for Chinese language processing. Howev- er, with the successive improvements, the standard metric is becoming hard to distin- guish state-of-the-art word segmentation systems. In …...

For many NLP applications that require a parser, the sentences of interest may not be well-formed. If the parser can overlook prob- lems such as grammar mistakes and produce a …...

. This paper proposes a new discriminative framework to train continuous-space trans- lation models based. This framework relies on the definition of a new objective function that al- lows us …...

AbstractThe 2017 Fake News Challenge Stage 1 (FNC-1) shared task addressed a stance classification task as a crucial first step towards detecting fake news. To date, there is no in-depth …...

In this paper, we present a framework to evaluate the human corrections of a speaker diarization. We propose four elementary actions to correct the diarization and an automaton to simulate …...

AbstractGenerative Adversarial Networks (GANs) are a promising approach for text generation that, unlike traditional language models (LM), does not suffer from the problem of “exposure bias”. However, A major hurdle …...

AbstractIn this paper, we present neural model architecture submitted to the SemEval-2019 Task 9 competition: “Suggestion Mining from Online Reviews and Forums”. We participated in both subtasks for domain specific …...

AbstractWhile pre-trained word embeddings have been shown to improve the performance of downstream tasks, many questions remain regarding their reliability: Do the same pre-trained word embeddings result in the best …...

AbstractApproaching named entities transliteration as a Neural Machine Translation (NMT) problem is common practice. While many have applied various NMT techniques to enhance machine transliteration models, few focus on the …...

AbstractExploiting the broad translation of the Bible into the world’s languages, we train and distribute morphosyntactic tools for approximately one thousand languages, vastly outstripping previous distributions of tools devoted to …...

AbstractRecent studies have revealed that reading comprehension (RC) systems learn to exploit annotation artifacts and other biases in current datasets. This prevents the community from reliably measuring the progress of …...

AbstractText structuring is a fundamental step in NLG, especially when generating multi-sentential text. With the goal of fostering more general and data-driven approaches to text structuring, we propose the new …...

AbstractWe describe our systems of subtask1 and subtask3 for SemEval-2021 Task 6 on Detection of Persuasion Techniques in Texts and Images. The purpose of subtask1 is to identify propaganda techniques …...

AbstractPrecisely assessing the progress in natural language generation (NLG) tasks is challenging, and human evaluation to establish a preference in a model’s output over another is often necessary. However, human …...

AbstractEvaluating Natural Language Generation (NLG) systems is a challenging task. Firstly, the metric should ensure that the generated hypothesis reflects the reference’s semantics. Secondly, it should consider the grammatical quality …...

Automatic generation of questions about the given context is useful for the adaptation of question-answering systems or to support edu- cation. We trained and evaluated a model that generates a …...

AbstractDue to the complex label hierarchy and intensive labeling cost in practice, the hierarchical text classification (HTC) suffers a poor performance especially when low-resource or few-shot settings are considered. Recently, …...

AbstractUnderstanding sentence semantics requires an interpretation of the main information from a concrete context. To investigate how individual word contributes to sentence semantics, we propose a perturbation method for unsupervised …...

AbstractExisting controllable dialogue generation work focuses on the single-attribute control and lacks generalization capability to out-of-distribution multiple attribute combinations. In this paper, we explore the compositional generalization for multi-attribute controllable …...