A5001721257- Speech and dialogue systems
- Speech Recognition and Synthesis
- Phonetics and Phonology Research
- Second Language Acquisition and Learning
- Intelligent Tutoring Systems and Adaptive Learning
- Face Recognition and Perception
- Social and Intergroup Psychology
- Psychology of Moral and Emotional Judgment
- Neural dynamics and brain function
- Linguistics, Language Diversity, and Identity
- Visual perception and processing mechanisms
- Experimental Behavioral Economics Studies
- Conflict Management and Negotiation
- Multiple Sclerosis Research Studies
- Advanced MRI Techniques and Applications
- Emotions and Moral Behavior
- Emotional Intelligence and Performance
- Multisensory perception and integration
- Ethics in Business and Education
- Digital Communication and Language
- Natural Language Processing Techniques
- Music and Audio Processing
- Neurological disorders and treatments
- Human Motion and Animation
Center for Translational Neurophysiology of Speech and Communication
2020-2023
Italian Institute of Technology
2020-2023
University of Ferrara
2020-2023
Google (United States)
2023
University of Glasgow
2020-2021
Humans can quickly recognize objects in a dynamically changing world. This ability is showcased by the fact that observers succeed at recognizing rapidly image sequences, up to 13 ms/image. To date, mechanisms govern dynamic object recognition remain poorly understood. Here, we developed deep learning models for and compared different computational mechanisms, contrasting feedforward recurrent, single-image sequential processing as well forms of adaptation. We found only integrate images...
We introduce the Alternating Reading Task (ART) Corpus, a collection of dyadic sentence reading for studying entrainment and imitation behaviour in speech communication. The ART corpus features three experimental conditions - solo reading, alternating deliberate as well sub-corpora encompassing French-, Italian-, Slovak-accented English. This design allows systematic investigation controlled less-spontaneous setting. Alongside detailed transcriptions, it includes English proficiency scores,...
Intergroup dynamics shape the ways in which we interact with other people. We feel more empathy towards ingroup members compared to outgroup members, and can even pleasure when an member experiences misfortune, known as schadenfreude. Here, test extent these intergroup biases emerge during interactions robots. measured trial-by-trial fluctuations emotional reactivity outcome of a competitive reaction time game assess both schadenfreude arbitrary human-human human-robot teams. Across four...
Abstract Humans can rapidly recognize objects in a dynamically changing world. This ability is showcased by the fact that observers succeed at recognizing image sequences, up to 13 ms/image. To date, mechanisms govern dynamic object recognition remain poorly understood. Here, we developed deep learning models for and compared different computational mechanisms, contrasting feedforward recurrent, single-image sequential processing as well forms of adaptation. We found only integrate images...
Phonetic convergence describes the automatic and unconscious speech adaptation of two interlocutors in a conversation.This paper proposes Siamese recurrent neural network (RNN) architecture to measure holistic spectral characteristics sounds an L2-L2 interaction.We extend alternating reading task (the ART) dataset by adding 20 native Slovak L2 English speakers.We train test RNN model phonetic from three different language groups: Italian (9 dyads), French (10 dyads) dyads).Our results...
Intergroup dynamics shape the ways in which we interact with other people. We feel more empathy towards ingroup members compared to outgroup members, and can even pleasure when an member experiences misfortune, known as schadenfreude. Here, test extent these intergroup biases emerge during interactions robots. measured trial-by-trial fluctuations emotional reactivity outcome of a competitive reaction time game assess both schadenfreude arbitrary human-human human-robot teams. Across four...
Phonetic convergence describes the automatic and unconscious speech adaptation of two interlocutors in a conversation. This paper proposes Siamese recurrent neural network (RNN) architecture to measure holistic spectral characteristics sounds an L2-L2 interaction. We extend alternating reading task (the ART) dataset by adding 20 native Slovak L2 English speakers. train test RNN model phonetic from three different language groups: Italian (9 dyads), French (10 dyads) dyads). Our results...