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Concept

Chatbot

Related publications (31)

User Expectations of Conversational Chatbots Based on Online Reviews

Pearl Pu Faltings, Ekaterina Svikhnushina

Open-domain chatbots that can engage in a conversation on any topic received significant attention in the last several years, which opened opportunities for studying user interaction with them. Drawing from reviews of chatbots posted on Google Play, we exp ...

ASSOC COMPUTING MACHINERY2021

Conveying the Perception of Humor Arising from Ambiguous Grammatical Constructs in Human-Chatbot Interaction

Denis Gillet, Juan Carlos Farah, Sandy Ingram

Chatbots have long been advocated for computer-assisted language learning systems to support learners with conversational practice. A particular challenge in such systems is explaining mistakes stemming from ambiguous grammatical constructs. Misplaced modi ...

2021

Towards versatile conversations with data-driven dialog management and its integration in commercial platforms

Pablo Cañas Castellanos

Conversational interfaces have recently become a ubiquitous element in both the personal sphere by easing access to services, and industrial environments by the automation of services, improved customer support and its corresponding cost savings. However, ...

2021

Smart Toys plus plus : Exploiting the Social Connectedness for Playing and Learning

Ayberk Özgür, Arzu Güneysu Özgür

Under the umbrella of smart toys, a myriad of interactive systems have addressed a variety of scenarios considering entertainment, education, sustainability, social and environmental learning through play. Tangibles and small toy robots prevail; but intera ...

ASSOC COMPUTING MACHINERY2021

Conversational Multi-Hop Reasoning with Neural Commonsense Knowledge and Symbolic Logic Rules

Antoine Bosselut

One 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 this paper, we propose a zeroshot commonsense reasoning system for c ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2021

Reservoir Computing meets Recurrent Kernels and Structured Transforms

Florent Gérard Krzakala, Jonathan Yuelin Dong

Reservoir Computing is a class of simple yet efficient Recurrent Neural Networks where internal weights are fixed at random and only a linear output layer is trained. In the large size limit, such random neural networks have a deep connection with kernel m ...

Curran Associates, Inc.2020

From Classical to Unsupervised-Deep-Learning Methods for Solving Inverse Problems in Imaging

Harshit Gupta

In this thesis, we propose new algorithms to solve inverse problems in the context of biomedical images. Due to ill-posedness, solving these problems require some prior knowledge of the statistics of the underlying images. The traditional algorithms, in th ...

EPFL2020

Building a Question-Answering Chatbot using Forum Data in the Semantic Space

Pierre Dillenbourg, Marc Laperrouza, Khalil Mrini

We build a conversational agent which knowledge base is an online forum for parents of autistic children. We collect about 35,000 threads totalling some 600,000 replies, and label 1% of them for usefulness using Amazon Mechanical Turk. We train a Random Fo ...

2018

Automatic Online Fake News Detection Combining Content and Social Signals

Stefano Moret

The proliferation and rapid diffusion of fake news on the Internet highlight the need of automatic hoax detection systems. In the context of social networks, machine learning (ML) methods can be used for this purpose. Fake news detection strategies are tra ...

IEEE2018

Joint Speaker Verification and Anti-Spoofing in the i-Vector Space

Sébastien Marcel

Any biometric recognizer is vulnerable to spoofing attacks and hence voice biometric, also called automatic speaker verification (ASV), is no exception; replay, synthesis, and conversion attacks all provoke false acceptances unless countermeasures are used ...

2015

Overlapping speech detection using long-term conversational features for speaker diarization in meeting room conversations

Hervé Bourlard, Sree Harsha Yella

Overlapping speech has been identified as one of the main sources of errors in diarization of meeting room conversations. Therefore, overlap detection has become an important step prior to speaker diarization. Studies on conversational analysis have shown ...

2014