research
∙
09/14/2023
Multilingual Audio Captioning using machine translated data
Automated Audio Captioning (AAC) systems attempt to generate a natural l...
share
research
∙
09/01/2023
CoNeTTE: An efficient Audio Captioning system leveraging multiple datasets with Task Embedding
Automated Audio Captioning (AAC) involves generating natural language de...
research
∙
08/29/2023
Killing two birds with one stone: Can an audio captioning system also be used for audio-text retrieval?
Automated Audio Captioning (AAC) aims to develop systems capable of desc...
research
∙
06/01/2023
Adapting a ConvNeXt model to audio classification on AudioSet
In computer vision, convolutional neural networks (CNN) such as ConvNeXt...
research
∙
06/01/2023
Dilated Convolution with Learnable Spacings: beyond bilinear interpolation
Dilated Convolution with Learnable Spacings (DCLS) is a recently propose...
research
∙
05/02/2023
Multitask learning in Audio Captioning: a sentence embedding regression loss acts as a regularizer
In this work, we propose to study the performance of a model trained wit...
research
∙
11/14/2022
Is my automatic audio captioning system so bad? spider-max: a metric to consider several caption candidates
Automatic Audio Captioning (AAC) is the task that aims to describe an au...
research
∙
06/09/2022
Audio-video fusion strategies for active speaker detection in meetings
Meetings are a common activity in professional contexts, and it remains ...
research
∙
12/07/2021
Dilated convolution with learnable spacings
Dilated convolution is basically a convolution with a wider kernel creat...
research
∙
03/04/2021
End-to-end acoustic modelling for phone recognition of young readers
Automatic recognition systems for child speech are lagging behind those ...
research
∙
03/01/2021
Fast threshold optimization for multi-label audio tagging using Surrogate gradient learning
Multi-label audio tagging consists of assigning sets of tags to audio re...
research
∙
02/16/2021
Improving Deep-learning-based Semi-supervised Audio Tagging with Mixup
Recently, semi-supervised learning (SSL) methods, in the framework of de...
research
∙
11/13/2020
Low-activity supervised convolutional spiking neural networks applied to speech commands recognition
Deep Neural Networks (DNNs) are the current state-of-the-art models in m...
research
∙
11/22/2019
Technical report: supervised training of convolutional spiking neural networks with PyTorch
Recently, it has been shown that spiking neural networks (SNNs) can be t...
research
∙
06/17/2019
Evaluation of post-processing algorithms for polyphonic sound event detection
Sound event detection (SED) aims at identifying audio events (audio tagg...
research
∙
01/10/2019
Cosine-similarity penalty to discriminate sound classes in weakly-supervised sound event detection
The design of new methods and models when only weakly-labeled data are a...
research
∙
10/30/2018
The Airbus Air Traffic Control speech recognition 2018 challenge: towards ATC automatic transcription and call sign detection
In this paper, we describe the outcomes of the challenge organized and r...
research
∙
07/08/2018