Publications associées à Spectrogramme

Filter-Informed Spectral Graph Wavelet Networks for Multiscale Feature Extraction and Intelligent Fault Diagnosis

Intelligent fault diagnosis has been increasingly improved with the evolution of deep learning (DL) approaches. Recently, the emerging graph neural networks (GNNs) have also been introduced in the field of fault diagnosis with the goal to make better use o ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach

Alexis Berne, Anne-Claire Marie Billault--Roux, Gionata Ghiggi

The use of meteorological radars to study snowfall microphysical properties and processes is well established, in particular via a few distinct techniques: the use of radar polarimetry, of multi-frequency radar measurements, and of the radar Doppler spectr ...

COPERNICUS GESELLSCHAFT MBH2023

Denoising and Raw-waveform Networks for Weakly-Supervised Gender Identification on Noisy Speech

Mathew Magimai Doss, Jilt Sebastian, Manoj Kumar

This paper presents a raw-waveform neural network and uses it along with a denoising network for clustering in weakly supervised learning scenarios under extreme noise conditions. Specifically, we consider language independent Automatic Gender Recognition ...

ISCA-INT SPEECH COMMUNICATION ASSOC2018

Towards directly modeling raw speech signal for speaker verification using CNNs

Sébastien Marcel, Hannah Muckenhirn

Speaker verification systems traditionally extract and model cepstral features or filter bank energies from the speech signal. In this paper, inspired by the success of neural network-based approaches to model directly raw speech signal for applications su ...

IEEE2018

Vertex-Frequency Analysis on Graphs

Pierre Vandergheynst, Benjamin Ricaud, David Shuman

One of the key challenges in the area of signal processing on graphs is to design dictionaries and transform methods to identify and exploit structure in signals on weighted graphs. To do so, we need to account for the intrinsic geometric structure of the ...

Academic Press Inc Elsevier Science2016

Real-Time Audio-Visual Analysis for Multiperson Videoconferencing

Hervé Bourlard, Jean-Marc Odobez, Petr Motlicek, Danil Korchagin

We describe the design of a system consisting of several state-of-the-art real-time audio and video processing components enabling multimodal stream manipulation (e.g., automatic online editing for multiparty videoconferencing applications) in open, uncons ...

2013

Spectrogram MPC: Enforcing hard constraints on system's output spectra

Colin Neil Jones, Melanie Nicole Zeilinger, Jean-Hubert Hours

A novel model predictive control (MPC) scheme that allows one to enforce hard constraints on the spectrum of a constrained system’s output signal is presented. The approach is based on a time-local analysis of the spectrum of output signals by means of the ...

Ieee Computer Soc2012

Wavelets on graphs via spectral graph theory

Pierre Vandergheynst, Rémi Gribonval

We propose a novel method for constructing wavelet transforms of functions defined on the vertices of an arbitrary finite weighted graph. Our approach is based on defining scaling using the the graph analogue of the Fourier domain, namely the spectral deco ...

Elsevier2011

Semi-Supervised Learning with Spectral Graph Wavelets

Pierre Vandergheynst, David Shuman, Mohammadjavad Faraji

We consider the transductive learning problem when the labels belong to a continuous space. Through the use of spectral graph wavelets, we explore the benefits of multiresolution analysis on a graph constructed from the labeled and unlabeled data. The spec ...

2011

Robustness of Group Delay Representations for Noisy Speech Signals

Sree Hari Krishnan Parthasarathi

This paper demonstrates the robustness of group delay based features to additive noise. First, we analytically show the robustness of group delay based represen- tations. The analysis makes use of the fact that, for minimum-phase signals, the group delay f ...

2011