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Publications associées (36)

Hearing structure in music: An empirical inquiry into listening as representation and processing

As a universal expression of human creativity, music is capable of conveying great subtlety and complexity. Crucially, this complexity is not encoded in the score or in the sounds, but is rather construed in the mind of the listener in the form of nuanced ...

EPFL2024

Studies showed that motor expertise was found to induce improvement in language processing. Grounded and situated approaches attributed this effect to an underlying automatic simulation of the motor experience elicited by action words, similar to motor ima ...

FRONTIERS MEDIA SA2023

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Music can be interpreted by attributing syntactic relationships to sequential musical events, and, computationally, such musical interpretation represents an analogous combinatorial task to syntactic processing in language. While this perspective has been ...

Hoboken2023

Kinesthetic motor-imagery training improves performance on lexical-semantic access

Sylvain Jean-François Harquel, Camille Bonnet

The objective of this study was to evaluate the effect of Motor Imagery (MI) training on language comprehension. In line with literature suggesting an intimate relationship between the language and the motor system, we proposed that a MI-training could imp ...

PUBLIC LIBRARY SCIENCE2022

Exploring the spatial resolution of TMS-EEG coupling on the sensorimotor region

Estelle Emeline Raffin, Sylvain Jean-François Harquel

The use of TMS-EEG coupling as a neuroimaging tool for the functional exploration of the human brain recently gained strong interest. If this tool directly inherits the fine temporal resolution from EEG, its spatial counterpart remains unknown. In this stu ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2022

Word-level Embeddings for Cross-Task Transfer Learning in Speech Processing

Milos Cernak, Pierre Anton Beckmann

Recent breakthroughs in deep learning often rely on representation learning and knowledge transfer. In recent years, unsupervised and self-supervised techniques for learning speech representation were developed to foster automatic speech recognition. Up to ...

EUROPEAN ASSOC SIGNAL SPEECH & IMAGE PROCESSING-EURASIP2021

The relationship between EEG and fMRI connectomes is reproducible across simultaneous EEG-fMRI studies from 1.5T to 7T

Rolf Gruetter, João Pedro Forjaco Jorge, Arwen Blanche Giraud, François Lazeyras, Giannina Rita Iannotti

Both electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are non-invasive methods that show complementary aspects of human brain activity. Despite measuring different proxies of brain activity, both the measured blood-oxygenation ...

2021

Jointly Optimizing Sensing Pipelines for Multimodal Mixed Reality Interaction

Lakmal Buddika Meegahapola

Natural human interactions for Mixed Reality Applications are overwhelmingly multimodal: humans communicate intent and instructions via a combination of visual, aural and gestural cues. However, supporting low-latency and accurate comprehension of such mul ...

IEEE COMPUTER SOC2020

Learning Entailment-Based Sentence Embeddings from Natural Language Inference

James Henderson, Rabeeh Karimi Mahabadi, Jan Frederik Jonas Florian Mai

Large datasets on natural language inference are a potentially valuable resource for inducing semantic representations of natural language sentences. But in many such models the embeddings computed by the sentence encoder goes through an MLP-based interact ...

Idiap2019

HMM-based Approaches to Model Multichannel Information in Sign Language inspired from Articulatory Features-based Speech Processing

Marzieh Razavi, Sandrine Tornay, Necati Cihan Camgöz

Sign language conveys information through multiple channels, such as hand shape, hand movement, and mouthing. Modeling this multi-channel information is a highly challenging problem. In this paper, we elucidate the link between spoken language and sign lan ...

IEEE2019

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