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Found 29 papers, 8 papers with code
Vers la compréhension automatique de la parole bout-en-bout à moindre effort (Towards automatic end-to-end speech understanding with less effort)
Les approches de compréhension automatique de la parole ont récemment bénéficié de l’apport de modèles préappris par autosupervision sur de gros corpus de parole.
Citation Context Classification: Critical vs Non-critical
In this work, we investigate how to automatically classify the critical citation contexts using Natural Language Processing (NLP).
Controllable Neural Natural Language Generation: comparison of state-of-the-art control strategies
In this paper, we study different strategies of control in triple-totext generation systems particularly from the aspects of text structure and text length.
Multi3Generation: Multitask, Multilingual, Multimodal Language Generation
This paper presents the Multitask, Multilingual, Multimodal Language Generation COST Action – Multi3Generation (CA18231), an interdisciplinary network of research groups working on different aspects of language generation.
Everything, Everywhere, All at Once: Is Mechanistic Interpretability Identifiable?
This work contributes to defining explanation standards in AI.
FedAli: Personalized Federated Learning with Aligned Prototypes through Optimal Transport
During local training, the ALP layer updates local prototypes and aligns embeddings toward global prototypes aggregated from all clients using our novel FL framework, Federated Alignment (FedAli).
Comparing Self-Supervised Learning Techniques for Wearable Human Activity Recognition
Although supervised learning methods are the most effective in this task, their effectiveness is constrained to using a large amount of labeled data during training.
Spoken Dialogue System for Medical Prescription Acquisition on Smartphone: Development, Corpus and Evaluation
In this paper, we present a natural language interface for e-prescribing software in the form of a spoken dialogue system accessible on a smartphone.
Can GPT models Follow Human Summarization Guidelines? Evaluating ChatGPT and GPT-4 for Dialogue Summarization
This study explores the capabilities of prompt-driven Large Language Models (LLMs) like ChatGPT and GPT-4 in adhering to human guidelines for dialogue summarization.
FRACAS: A FRench Annotated Corpus of Attribution relations in newS
Quotation extraction is a widely useful task both from a sociological and from a Natural Language Processing perspective.
PSentScore: Evaluating Sentiment Polarity in Dialogue Summarization
Automatic dialogue summarization is a well-established task with the goal of distilling the most crucial information from human conversations into concise textual summaries.
Combining Public Human Activity Recognition Datasets to Mitigate Labeled Data Scarcity
In this paper, we propose a novel strategy to combine publicly available datasets with the goal of learning a generalized HAR model that can be fine-tuned using a limited amount of labeled data on an unseen target domain.
Evaluation and comparison of federated learning algorithms for Human Activity Recognition on smartphones
Unfortunately, however, the most popular federated learning algorithms have been shown not to be adapted to some highly heterogeneous pervasive computing environments.
Lightweight Transformers for Human Activity Recognition on Mobile Devices
Human Activity Recognition (HAR) on mobile devices has shown to be achievable with lightweight neural models learned from data generated by the user's inertial measurement units (IMUs).
A Spoken Drug Prescription Dataset in French for Spoken Language Understanding
To facilitate the research and development of spoken medical dialogue systems, we present, to the best of our knowledge, the first spoken medical drug prescriptions corpus, named PxSLU.
End-to-End Spoken Language Understanding: Performance analyses of a voice command task in a low resource setting
In this paper, we present a study identifying the signal features and other linguistic properties used by an E2E model to perform the SLU task.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Effectiveness of French Language Models on Abstractive Dialogue Summarization Task
We further discuss the limits of such pre-trained models and the challenges that must be addressed for summarizing spontaneous dialogues.
Federated Self-Supervised Learning in Heterogeneous Settings: Limits of a Baseline Approach on HAR
In the case of supervised learning, labeling is entrusted to the clients.
Federated Continual Learning through distillation in pervasive computing
Current solutions rely on the availability of large amounts of stored data at the client side in order to fine-tune the models sent by the server.
Federated Learning and catastrophic forgetting in pervasive computing: demonstration in HAR domain
Federated Learning has been introduced as a new machine learning paradigm enhancing the use of local devices.
Vers la compréhension automatique de la parole bout-en-bout à moindre effort
Recent advances in spoken language understanding benefited from Self-Supervised models trained on large speech corpora.
Toward Low-Cost End-to-End Spoken Language Understanding
Recent advances in spoken language understanding benefited from Self-Supervised models trained on large speech corpora.
GenderedNews: Une approche computationnelle des écarts de représentation des genres dans la presse française
We then detail the methods adopted by {\it GenderedNews} and the two metrics implemented: the masculinity rate of mentions and the proportion of men quoted in online news.
Neural Medication Extraction: A Comparison of Recent Models in Supervised and Semi-supervised Learning Settings
This is why the medication extraction task has emerged.
A Federated Learning Aggregation Algorithm for Pervasive Computing: Evaluation and Comparison
About this, Federated Learning has been recently proposed for distributed model training in the edge.
A distillation-based approach integrating continual learning and federated learning for pervasive services
Federated Learning, a new machine learning paradigm enhancing the use of edge devices, is receiving a lot of attention in the pervasive community to support the development of smart services.
Semi-Supervised Neural Text Generation by Joint Learning of Natural Language Generation and Natural Language Understanding Models
These findings open the way to the exploitation of non-annotated datasets which is the current bottleneck for the E2E NLG system development to new applications.
Arcades: A deep model for adaptive decision making in voice controlled smart-home
In a voice-controlled smart-home, a controller must respond not only to user's requests but also according to the interaction context.
Etude de la performance des modèles acoustiques pour des voix de personnes âgées en vue de l'adaptation des systèmes de RAP (Assessment of the acoustic models performance in the ageing voice case for ASR system adaptation) [in French]
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
