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Found 24 papers, 3 papers with code
Correction automatique d’examens écrits par approche neuronale profonde et attention croisée bidirectionnelle (Deep Neural Networks and Bidirectional Cross-Attention for Automatic Answer Grading)
Nous proposons trois systèmes de classification reposant sur des caractéristiques extraites de plongements de mots contextuels issus d’un modèle BERT (CamemBERT).
Far-Field Speaker Recognition Benchmark Derived From The DiPCo Corpus
The main goal of this corpus is to foster research in far-field and multi-channel text-independent speaker verification.
Asymmetric and trial-dependent modeling: the contribution of LIA to SdSV Challenge Task 2
The SdSv challenge Task 2 provided an opportunity to assess efficiency and robustness of modern text-independent speaker verification systems.
Probing the Information Encoded in Neural-based Acoustic Models of Automatic Speech Recognition Systems
Following many researches in neural networks interpretability, we propose in this article a protocol that aims to determine which and where information is located in an ASR acoustic model (AM).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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How Important Is Tokenization in French Medical Masked Language Models?
Subword tokenization has become the prevailing standard in the field of natural language processing (NLP) over recent years, primarily due to the widespread utilization of pre-trained language models.
DrBenchmark: A Large Language Understanding Evaluation Benchmark for French Biomedical Domain
This limitation hampers the evaluation of the latest French biomedical models, as they are either assessed on a minimal number of tasks with non-standardized protocols or evaluated using general downstream tasks.
BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains
This marks the first large-scale multilingual evaluation of LLMs in the medical domain.
LeBenchmark 2.0: a Standardized, Replicable and Enhanced Framework for Self-supervised Representations of French Speech
Self-supervised learning (SSL) is at the origin of unprecedented improvements in many different domains including computer vision and natural language processing.
A Zero-shot and Few-shot Study of Instruction-Finetuned Large Language Models Applied to Clinical and Biomedical Tasks
We evaluate four state-of-the-art instruction-tuned large language models (LLMs) -- ChatGPT, Flan-T5 UL2, Tk-Instruct, and Alpaca -- on a set of 13 real-world clinical and biomedical natural language processing (NLP) tasks in English, such as named-entity recognition (NER), question-answering (QA), relation extraction (RE), etc.
FrenchMedMCQA: A French Multiple-Choice Question Answering Dataset for Medical domain
This paper introduces FrenchMedMCQA, the first publicly available Multiple-Choice Question Answering (MCQA) dataset in French for medical domain.
DrBERT: A Robust Pre-trained Model in French for Biomedical and Clinical domains
In recent years, pre-trained language models (PLMs) achieve the best performance on a wide range of natural language processing (NLP) tasks.
I4U System Description for NIST SRE'20 CTS Challenge
This manuscript describes the I4U submission to the 2020 NIST Speaker Recognition Evaluation (SRE'20) Conversational Telephone Speech (CTS) Challenge.
Speech Resources in the Tamasheq Language
In this paper we present two datasets for Tamasheq, a developing language mainly spoken in Mali and Niger.
Studying squeeze-and-excitation used in CNN for speaker verification
A channel attention mechanism, called squeeze-and-excitation (SE), has recently been proposed in convolution layers and applied to speaker verification.
Study on the temporal pooling used in deep neural networks for speaker verification
The x-vector architecture has recently achieved state-of-the-art results on the speaker verification task.
ON-TRAC Consortium End-to-End Speech Translation Systems for the IWSLT 2019 Shared Task
This paper describes the ON-TRAC Consortium translation systems developed for the end-to-end model task of IWSLT Evaluation 2019 for the English-to-Portuguese language pair.
I4U Submission to NIST SRE 2018: Leveraging from a Decade of Shared Experiences
The I4U consortium was established to facilitate a joint entry to NIST speaker recognition evaluations (SRE).
LIA at SemEval-2017 Task 4: An Ensemble of Neural Networks for Sentiment Classification
This paper describes the system developed at LIA for the SemEval-2017 evaluation campaign.
Building a robust sentiment lexicon with (almost) no resource
Creating sentiment polarity lexicons is labor intensive.
Fusion d'espaces de repr\'esentations multimodaux pour la reconnaissance du r\^ole du locuteur dans des documents t\'el\'evisuels (Multimodal embedding fusion for robust speaker role recognition in video broadcast )
L{'}identification du r{\^o}le d{'}un locuteur dans des {\'e}missions de t{\'e}l{\'e}vision est un probl{\`e}me de classification de personne selon une liste de r{\^o}les comme pr{\'e}sentateur, journaliste, invit{\'e}, etc.
