Search Results for author: Giuseppe Riccardi

Found 43 papers, 11 papers with code

Interpretable SincNet-based Deep Learning for Emotion Recognition from EEG brain activity

1 code implementation18 Jul 2021 Juan Manuel Mayor-Torres, Mirco Ravanelli, Sara E. Medina-DeVilliers, Matthew D. Lerner, Giuseppe Riccardi

This result is consistent with recent neuroscience studies on emotion recognition, which found an association between these band suppressions and the behavioral deficits observed in individuals with ASD.

EEG Electroencephalogram (EEG) +1

ISO-Standard Domain-Independent Dialogue Act Tagging for Conversational Agents

1 code implementation COLING 2018 Stefano Mezza, Alessandra Cervone, Giuliano Tortoreto, Evgeny A. Stepanov, Giuseppe Riccardi

Dialogue Act (DA) tagging is crucial for spoken language understanding systems, as it provides a general representation of speakers' intents, not bound to a particular dialogue system.

General Classification Spoken Language Understanding

Evaluation of Interpretability for Deep Learning algorithms in EEG Emotion Recognition: A case study in Autism

1 code implementation25 Nov 2021 Juan Manuel Mayor-Torres, Sara Medina-DeVilliers, Tessa Clarkson, Matthew D. Lerner, Giuseppe Riccardi

This study is the first to consolidate a more transparent feature-relevance calculation for a successful EEG-based facial emotion recognition using a within-subject-trained CNN in typically-developed and ASD individuals.

EEG EEG Emotion Recognition +4

Coherence Models for Dialogue

1 code implementation21 Jun 2018 Alessandra Cervone, Evgeny Stepanov, Giuseppe Riccardi

Nevertheless, both the original grid and its extensions do not model intents, a crucial aspect that has been studied widely in the literature in connection to dialogue structure.

Let's Give a Voice to Conversational Agents in Virtual Reality

1 code implementation4 Aug 2023 Michele Yin, Gabriel Roccabruna, Abhinav Azad, Giuseppe Riccardi

In this work, we present an open-source architecture with the goal of simplifying the development of conversational agents operating in virtual environments.

Unity

Annotating and Modeling Empathy in Spoken Conversations

no code implementations13 May 2017 Firoj Alam, Morena Danieli, Giuseppe Riccardi

The automatic classification system was evaluated on call center conversations where it showed significantly better performance than the baseline.

General Classification

Depression Severity Estimation from Multiple Modalities

no code implementations10 Nov 2017 Evgeny Stepanov, Stephane Lathuiliere, Shammur Absar Chowdhury, Arindam Ghosh, Radu-Laurentiu Vieriu, Nicu Sebe, Giuseppe Riccardi

In this AVEC challenge we explore different modalities (speech, language and visual features extracted from face) to design and develop automatic methods for the detection of depression.

Functions of Silences towards Information Flow in Spoken Conversation

no code implementations WS 2017 Shammur Absar Chowdhury, Evgeny Stepanov, Morena Danieli, Giuseppe Riccardi

It is also observed that sometimes long silences can be used deliberately to get a forced response from another speaker thus making silence a multi-functional and an important catalyst towards information flow.

Clustering

How Interlocutors Coordinate with each other within Emotional Segments?

no code implementations COLING 2016 Firoj Alam, Shammur Absar Chowdhury, Morena Danieli, Giuseppe Riccardi

In this paper, we aim to investigate the coordination of interlocutors behavior in different emotional segments.

The Development of the Multilingual LUNA Corpus for Spoken Language System Porting

no code implementations LREC 2014 Evgeny Stepanov, Giuseppe Riccardi, Ali Orkan Bayer

We discuss the challenges of the manual creation of multilingual corpora, as well as present the algorithms for the creation of multilingual SLU via Statistical Machine Translation (SMT).

Machine Translation Speech Synthesis +2

Improving the Recall of a Discourse Parser by Constraint-based Postprocessing

no code implementations LREC 2012 Sucheta Ghosh, Richard Johansson, Giuseppe Riccardi, Sara Tonelli

We describe two constraint-based methods that can be used to improve the recall of a shallow discourse parser based on conditional random field chunking.

Chunking Semantic Role Labeling

Modeling user context for valence prediction from narratives

no code implementations9 May 2019 Aniruddha Tammewar, Alessandra Cervone, Eva-Maria Messner, Giuseppe Riccardi

Automated prediction of valence, one key feature of a person's emotional state, from individuals' personal narratives may provide crucial information for mental healthcare (e. g. early diagnosis of mental diseases, supervision of disease course, etc.).

An Incremental Turn-Taking Model For Task-Oriented Dialog Systems

2 code implementations28 May 2019 Andrei C. Coman, Koichiro Yoshino, Yukitoshi Murase, Satoshi Nakamura, Giuseppe Riccardi

To identify the point of maximal understanding in an ongoing utterance, we a) implement an incremental Dialog State Tracker which is updated on a token basis (iDST) b) re-label the Dialog State Tracking Challenge 2 (DSTC2) dataset and c) adapt it to the incremental turn-taking experimental scenario.

dialog state tracking

Transfer of Corpus-Specific Dialogue Act Annotation to ISO Standard: Is it worth it?

no code implementations LREC 2016 Shammur Absar Chowdhury, Evgeny Stepanov, Giuseppe Riccardi

In this paper we test the utility of the ISO standard through comparative evaluation of the corpus-specific legacy and the semi-automatically transferred DiAML DA annotations on supervised dialogue act classification task.

Classification Dialogue Act Classification +1

Multilevel Annotation of Agreement and Disagreement in Italian News Blogs

no code implementations LREC 2016 Fabio Celli, Giuseppe Riccardi, Firoj Alam

In this paper, we present a corpus of news blog conversations in Italian annotated with gold standard agreement/disagreement relations at message and sentence levels.

Sentence

Affective Behaviour Analysis of On-line User Interactions: Are On-line Support Groups more Therapeutic than Twitter?

no code implementations WS 2019 Giuliano Tortoreto, Evgeny A. Stepanov, Alessandra Cervone, Mateusz Dubiel, Giuseppe Riccardi

Possible applications of the method include provision of guidelines that highlight potential implications of using such platforms on users' mental health, and/or support in the analysis of their impact on specific individuals.

Annotation of Emotion Carriers in Personal Narratives

no code implementations LREC 2020 Aniruddha Tammewar, Alessandra Cervone, Eva-Maria Messner, Giuseppe Riccardi

We are interested in the problem of understanding personal narratives (PN) - spoken or written - recollections of facts, events, and thoughts.

Emotion Carrier Recognition from Personal Narratives

no code implementations17 Aug 2020 Aniruddha Tammewar, Alessandra Cervone, Giuseppe Riccardi

In this work, we propose a novel task for Narrative Understanding: Emotion Carrier Recognition (ECR).

Emotion Classification Emotion Recognition

Detecting Emotion Carriers by Combining Acoustic and Lexical Representations

no code implementations13 Dec 2021 Sebastian P. Bayerl, Aniruddha Tammewar, Korbinian Riedhammer, Giuseppe Riccardi

However, in this work, we focus on Emotion Carriers (EC) defined as the segments (speech or text) that best explain the emotional state of the narrator ("loss of father", "made me choose").

Emotion Recognition Natural Language Understanding +1

What can Speech and Language Tell us About the Working Alliance in Psychotherapy

no code implementations17 Jun 2022 Sebastian P. Bayerl, Gabriel Roccabruna, Shammur Absar Chowdhury, Tommaso Ciulli, Morena Danieli, Korbinian Riedhammer, Giuseppe Riccardi

To the best of our knowledge, this is the first and a novel study to exploit speech and language for characterising working alliance.

Whats New? Identifying the Unfolding of New Events in Narratives

no code implementations15 Feb 2023 Seyed Mahed Mousavi, Shohei Tanaka, Gabriel Roccabruna, Koichiro Yoshino, Satoshi Nakamura, Giuseppe Riccardi

We publish the annotated dataset, annotation materials, and machine learning baseline models for the task of new event extraction for narrative understanding.

Event Extraction Sentence

Response Generation in Longitudinal Dialogues: Which Knowledge Representation Helps?

no code implementations25 May 2023 Seyed Mahed Mousavi, Simone Caldarella, Giuseppe Riccardi

Dialogue systems designed for LDs should uniquely interact with the users over multiple sessions and long periods of time (e. g. weeks), and engage them in personal dialogues to elaborate on their feelings, thoughts, and real-life events.

Response Generation Text Generation

Understanding Emotion Valence is a Joint Deep Learning Task

no code implementations27 May 2023 Gabriel Roccabruna, Seyed Mahed Mousavi, Giuseppe Riccardi

We further observed that the discriminative model achieves the best trade-off of valence and EC prediction tasks in the joint prediction setting.

Multi-Task Learning

Are LLMs Robust for Spoken Dialogues?

no code implementations4 Jan 2024 Seyed Mahed Mousavi, Gabriel Roccabruna, Simone Alghisi, Massimo Rizzoli, Mirco Ravanelli, Giuseppe Riccardi

Large Pre-Trained Language Models have demonstrated state-of-the-art performance in different downstream tasks, including dialogue state tracking and end-to-end response generation.

Dialogue State Tracking Response Generation

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