Publications associées à Dialogue system

Generative AI-Enabled Conversational Interaction to Support Self-Directed Learning Experiences in Transversal Computational Thinking

Denis Gillet, Juan Carlos Farah, Adrian Christian Holzer, Abdessalam Ouaazki

As computational thinking (CT) becomes increasingly acknowledged as an important skill in education, self-directed learning (SDL) emerges as a key strategy for developing this capability. The advent of generative AI (GenAI) conversational agents has disrup ...

2024

A Conceptual Framework for Integrating Conversational Agents in Digital Education

Juan Carlos Farah

The presence of conversational agents (or chatbots) in educational contexts has been steadily increasing over the past few years. Recent surveys have shown widespread interest in the use of chatbots in education, both for research and practice. Although th ...

EPFL2023

Towards Novel Evaluation Methods for Social Dialog Systems

Ekaterina Svikhnushina

Language has shaped human evolution and led to the desire to endow machines with language abilities. Recent advancements in natural language processing enable us to achieve this breakthrough in human-machine interaction. However, introducing conversational ...

EPFL2023

Empathetic Conversational Agents for Distress Support

Kalpani Anuradha Welivita

Due to the increasing demands of today's fast-paced world, mental health concerns are on the rise, which necessitates innovative approaches to provide support to those in need. Open-domain conversational agents known as chatbots, offer a unique opportunit ...

EPFL2023

Towards Empathetic Open-Domain Chatbots

Yubo Xie

The research community of dialog generation has been interested in incorporating emotional information into the design of open-domain dialog systems ever since neural networks (sequence-to-sequence models in particular) were adopted for modeling dialogs. T ...

EPFL2022

PEACE: A Model of Key Social and EmotionalQualities of Conversational Chatbots

Pearl Pu Faltings, Ekaterina Svikhnushina

Open-domain chatbots engage with users in natural conversations to socialize and establish bonds. However, designing and developing an effective open-domain chatbot is challenging. It is unclear what qualities of a chatbot most correspond to users' expecta ...

ASSOC COMPUTING MACHINERY2022

Memory-Based Model Editing at Scale

Antoine Bosselut

Even the largest neural networks make errors, and once-correct predictions can become invalid as the world changes. Model editors make local updates to the behavior of base (pre-trained) models to inject updated knowledge or correct undesirable behaviors. ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2022

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

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

A Comparison of Methods for OOV-Word Recognition on a New Public Dataset

Petr Motlicek

A common problem for automatic speech recognition systems is how to recognize words that they did not see during training. Currently there is no established method of evaluating different techniques for tackling this problem. We propose using the CommonVoi ...

IEEE Signal Processing Society2021

Key Qualities of Conversational Chatbots - the PEACE Model

Pearl Pu Faltings, Ekaterina Svikhnushina

Open-domain chatbots engage in natural conversations with the user to socialize and establish bonds. However, designing and developing an effective open-domain chatbot is challenging. It is unclear what qualities of such chatbots most correspond to users' ...

ASSOC COMPUTING MACHINERY2021

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

Multilingual Training and Adaptation in Speech Recognition

Sibo Tong

State-of-the-art acoustic models for Automatic Speech Recognition (ASR) are based on Hidden Markov Models (HMM) and Deep Neural Networks (DNN) and often require thousands of hours of transcribed speech data during training. Therefore, building multilingual ...

EPFL2020

Haptic feedback perception and learning with cable-driven guidance in exosuit teleoperation of a simulated drone

Dario Floreano, Auke Ijspeert, Amy Roning Wu, Vivek Ramachandran, Carine Rognon

Robotics teleoperation enables human operators to control the movements of distally located robots. The development of new wearable interfaces as alternatives to hand-held controllers has created new modalities of control, which are more intuitive to use. ...

2019

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

NeuroSpeech: An open-source software for Parkinson's speech analysis

Milos Cernak

A new software for modeling pathological speech signals is presented in this paper. The software is called NeuroSpeech. This software enables the analysis of pathological speech signals considering different speech dimensions: phonation, articulation, pros ...

2018

On Modeling the Synergy Between Acoustic and Lexical Information for Pronunciation Lexicon Development

Marzieh Razavi

State-of-the-art automatic speech recognition (ASR) and text-to-speech systems require a pronunciation lexicon that maps each word to a sequence of phones. Manual development of lexicons is costly as it needs linguistic knowledge and human expertise. To fa ...

EPFL2017

Speaker diarization of spontaneous meeting room conversations

Sree Harsha Yella

Speaker diarization is the task of identifying ``who spoke when'' in an audio stream containing multiple speakers. This is an unsupervised task as there is no a priori information about the speakers. Diagnostical studies on state-of-the-art diarization sys ...

EPFL2015

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

Grapheme-based Automatic Speech Recognition using Probabilistic Lexical Modeling

Ramya Rasipuram

Automatic speech recognition (ASR) systems incorporate expert knowledge of language or the linguistic expertise through the use of phone pronunciation lexicon (or dictionary) where each word is associated with a sequence of phones. The creation of phone pr ...

EPFL2014