User Study

This paper describes SCANMail, a system that allows users to browse and search their voicemail messages by content through a GUI. Content based navigation is realized by use of automatic …...

We present and compare two approaches to the task of summarizing evaluative ar- guments. The first is a sentence extraction- based approach while the second is a lan- guage generation-based …...

Pictorial communication systems convert natural language text into pictures to as- sist people with limited literacy. We define a novel and challenging problem: picture layout optimization. Given an input sen- …...

AbstractAggregation of long lists of concepts is important to avoid overwhelming a small display. Focusing on the domain of mobile local search, this paper presents the development of an application …...

Music Recommendation Systems often recommend individual songs, as opposed to entire albums. The challenge is to gen- erate reviews for each song, since only full album reviews are available on-line. …...

AbstractAmbient Assisted Living (AAL) is the name for a European technology and innovation funding programme. AAL research field is about intelligent assistant systems for a healthier and safer life in …...

This paper describes a user study where hu- mans interactively train automatic text clas- sifiers. We attempt to replicate previous re- sults using multiple “average” Internet users instead of a …...

AbstractManual annotation of large textual corpora can be cost-prohibitive, especially for rare and under-resourced languages. One potential solution is pre-annotation: asking human annotators to correct sentences that have already been …...

AbstractUsers will interact with an individual app on smart devices (e.g., phone, TV, car) to fulfill a specific goal (e.g. find a photographer), but users may also pursue more complex …...

AbstractComputer-assisted transcription promises high-quality speech transcription at reduced costs. This is achieved by limiting human effort to transcribing parts for which automatic transcription quality is insufficient. Our goal is to …...

AbstractWe examine the task of aggregation in the context of text-to-text generation. We introduce a new aggregation task which frames the process as grouping input sentence fragments into clusters that …...

AbstractInteractive topic models are powerful tools for those seeking to understand large collections of text. However, existing sampling-based interactive topic modeling approaches scale poorly to large data sets. Anchor methods, …...

Automatic Speech Recognition (ASR) systems typically degrade in performance when recognizing an accent different from the accents in the training data. One way to overcome this problem without training new …...

The task of selecting suitable fonts for a given text is non-trivial, as tens of thousands of fonts are available, and the choice of font has been shown to affect …...

AbstractWe propose two novel manipulation strategies for increasing and decreasing the difficulty of C-tests automatically. This is a crucial step towards generating learner-adaptive exercises for self-directed language learning and preparing …...

AbstractIn the translation industry, human experts usually supervise and post-edit machine translation hypotheses. Adaptive neural machine translation systems, able to incrementally update the underlying models under an online learning regime, …...

AbstractSpoken languages are ever-changing, with new words entering them all the time. However, coming up with new words (neologisms) today relies exclusively on human creativity. In this paper we propose …...

AbstractWe address the problem of multimodal spatial understanding by decoding a set of language-expressed spatial relations to a set of 2D spatial arrangements in a multi-object and multi-relationship setting. We …...

AbstractApproaching new data can be quite deterrent; you do not know how your categories of interest are realized in it, commonly, there is no labeled data at hand, and the …...

AbstractPrevious research has found that task-oriented conversational agents are perceived more positively by users when they provide information in an empathetic manner compared to a plain, emotionless information exchange. However, …...

AbstractOne of the challenges faced by conversational agents is their inability to identify unstated presumptions of their users’ commands, a task trivial for humans due to their common sense. In …...

AbstractHumans are increasingly interacting with machines through language, sometimes in contexts where the user may not know they are talking to a machine (like over the phone or a text …...

AbstractSocratic questioning is an educational method that allows students to discover answers to complex problems by asking them a series of thoughtful questions. Generation of didactically sound questions is challenging, …...

AbstractMachine-in-the-loop writing aims to build models that assist humans to accomplish their writing tasks more effectively. Prior work has found that providing users a machine-written draft or sentence-level continuations has …...

This paper presents a new human-in-the- loop text classification framework with no labeled data incorporating weak supervision and Bayesian active learning with a seman- tic clustering constraint. Labeling function (LF)-based …...

AbstractAn audience’s prior beliefs and morals are strong indicators of how likely they will be affected by a given argument. Utilizing such knowledge can help focus on shared values to …...

AbstractMost Neural Topic Models (NTM) use a variational auto-encoder framework producing K topics limited to the size of the encoder’s output. These topics are interpreted through the selection of the …...

AbstractLong-form question answering systems provide rich information by presenting paragraph-level answers, often containing optional background or auxiliary information. While such comprehensive answers are helpful, not all information is required to …...

AbstractAutomated coherence metrics constitute an important and popular way to evaluate topic models. Previous works present a mixed picture of their presumed correlation with human judgement. In this paper, we …...

AbstractDesigning dialog tutors has been challenging as it involves modeling the diverse and complex pedagogical strategies employed by human tutors. Although there have been significant recent advances in neural conversational …...