Search Results for author:
Found 39 papers, 13 papers with code
Meta-learning for Classifying Previously Unseen Data Source into Previously Unseen Emotional Categories
In this paper, we place ourselves in a classification scenario in which the target classes and data type are not accessible during training.
Opinions in Interactions : New Annotations of the SEMAINE Database
In this paper, we present the process we used in order to collect new annotations of opinions over the multimodal corpus SEMAINE composed of dyadic interactions.
Code-switched inspired losses for spoken dialog representations
Spoken dialogue systems need to be able to handle both multiple languages and multilinguality inside a conversation (e. g in case of code-switching).
Méta-apprentissage : classification de messages en catégories émotionnelles inconnues en entraînement (Meta-learning : Classifying Messages into Unseen Emotional Categories)
Dans cet article nous reproduisons un scénario d’apprentissage selon lequel les données cibles ne sont pas accessibles et seules des données connexes le sont.
Polysemy in Spoken Conversations and Written Texts
Our discourses are full of potential lexical ambiguities, due in part to the pervasive use of words having multiple senses.
One Word, Two Sides: Traces of Stance in Contextualized Word Representations
The way we use words is influenced by our opinion.
EZCAT: an Easy Conversation Annotation Tool
We also present our first usage of EZCAT along with our annotation schema we used to annotate confidential customer service conversations.
"You might think about slightly revising the title”: Identifying Hedges in Peer-tutoring Interactions
Hedges have an important role in the management of rapport.
The Impact of Word Splitting on the Semantic Content of Contextualized Word Representations
When deriving contextualized word representations from language models, a decision needs to be made on how to obtain one for out-of-vocabulary (OOV) words that are segmented into subwords.
Automatic Analysis of Substantiation in Scientific Peer Reviews
With the increasing amount of problematic peer reviews in top AI conferences, the community is urgently in need of automatic quality control measures.
MAFALDA: A Benchmark and Comprehensive Study of Fallacy Detection and Classification
We introduce MAFALDA, a benchmark for fallacy classification that merges and unites previous fallacy datasets.
The Curious Decline of Linguistic Diversity: Training Language Models on Synthetic Text
This study investigates the consequences of training language models on synthetic data generated by their predecessors, an increasingly prevalent practice given the prominence of powerful generative models.
When to generate hedges in peer-tutoring interactions
This paper explores the application of machine learning techniques to predict where hedging occurs in peer-tutoring interactions.
How About Kind of Generating Hedges using End-to-End Neural Models?
Hedging is a strategy for softening the impact of a statement in conversation.
"You might think about slightly revising the title": identifying hedges in peer-tutoring interactions
Hedges play an important role in the management of conversational interaction.
Fillers in Spoken Language Understanding: Computational and Psycholinguistic Perspectives
Disfluencies (i. e. interruptions in the regular flow of speech), are ubiquitous to spoken discourse.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Questioning the Validity of Summarization Datasets and Improving Their Factual Consistency
Due to this lack of well-defined formulation, a large number of popular abstractive summarization datasets are constructed in a manner that neither guarantees validity nor meets one of the most essential criteria of summarization: factual consistency.
Of Human Criteria and Automatic Metrics: A Benchmark of the Evaluation of Story Generation
However, there is no consensus on which human evaluation criteria to use, and no analysis of how well automatic criteria correlate with them.
Representation Learning of Image Schema
Therefore, after obtaining the vector representation of the image schemas, we calculate the distances between those vectors.
A survey of neural models for the automatic analysis of conversation: Towards a better integration of the social sciences
In this paper we survey these neural architectures and what they have been applied to.
Don't Judge Me by My Face : An Indirect Adversarial Approach to Remove Sensitive Information From Multimodal Neural Representation in Asynchronous Job Video Interviews
In this article, we propose a new adversarial approach to remove sensitive information from the latent representation of neural networks without the need to collect any sensitive variable.
Beam Search with Bidirectional Strategies for Neural Response Generation
Sequence-to-sequence neural networks have been widely used in language-based applications as they have flexible capabilities to learn various language models.
Few-Shot Emotion Recognition in Conversation with Sequential Prototypical Networks
We test this method on two datasets with different languages: daily conversations in English and customer service chat conversations in French.
Emotion Classification
Emotion Recognition in Conversation
+1
Reasoning with Transformer-based Models: Deep Learning, but Shallow Reasoning
Recent years have seen impressive performance of transformer-based models on different natural language processing tasks.
Studying Alignment in a Collaborative Learning Activity via Automatic Methods: The Link Between What We Say and Do
We also find that well-performing teams verbalise the marker "oh" more when they are behaviourally aligned, compared to other times in the dialogue; showing that this marker is an important cue in alignment.
Learning to Disentangle Textual Representations and Attributes via Mutual Information
Learning disentangled representations of textual data is essential for many natural language tasks such as fair classification (\textit{e. g.} building classifiers whose decisions cannot disproportionately hurt or benefit specific groups identified by sensitive attributes), style transfer and sentence generation, among others.
The importance of fillers for text representations of speech transcripts
While being an essential component of spoken language, fillers (e. g."um" or "uh") often remain overlooked in Spoken Language Understanding (SLU) tasks.
Sequence-to-Sequence Predictive Model: From Prosody To Communicative Gestures
Our objective is to predict the timing of gestures according to the acoustic.
On-the-fly Detection of User Engagement Decrease in Spontaneous Human-Robot Interaction, International Journal of Social Robotics, 2019
In this paper, we consider the detection of a decrease of engagement by users spontaneously interacting with a socially assistive robot in a public space.
Human-Computer Interaction Robotics
Heavy-tailed Representations, Text Polarity Classification & Data Augmentation
The dominant approaches to text representation in natural language rely on learning embeddings on massive corpora which have convenient properties such as compositionality and distance preservation.
Ranked #3 on
Sentiment Analysis
on Yelp Binary classification
Slices of Attention in Asynchronous Video Job Interviews
In this paper, we focus on studying influential non verbal social signals in asynchronous job video interviews that are discovered by deep learning methods.
From the Token to the Review: A Hierarchical Multimodal approach to Opinion Mining
The task of predicting fine grained user opinion based on spontaneous spoken language is a key problem arising in the development of Computational Agents as well as in the development of social network based opinion miners.
HireNet: a Hierarchical Attention Model for the Automatic Analysis of Asynchronous Video Job Interviews
As part of a project to help recruiters, we collected a corpus of more than 7000 candidates having asynchronous video job interviews for real positions and recording videos of themselves answering a set of questions.
A multimodal movie review corpus for fine-grained opinion mining
We introduce specific categories in order to make the annotation of opinions easier for movie reviews.
Opinion Dynamics Modeling for Movie Review Transcripts Classification with Hidden Conditional Random Fields
This model allows us to capture the dynamics of the reviewer's opinion in the transcripts of long unsegmented audio reviews that are analyzed by our system.
Structured Output Learning with Abstention: Application to Accurate Opinion Prediction
Motivated by Supervised Opinion Analysis, we propose a novel framework devoted to Structured Output Learning with Abstention (SOLA).
Comparative analysis of verbal alignment in human-human and human-agent interactions
Engagement is an important feature in human-human and human-agent interaction.
