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Convolutional Recurrent Neural Networks for Polyphonic Sound Event Detection [PDF]
IEEE/ACM Transactions on Audio Speech and Language Processing, 2017 Sound events often occur in unstructured environments where they exhibit wide variations in their frequency content and temporal structure. Convolutional neural networks (CNN) are able to extract higher level features that are invariant to local spectral
Heittola, Toni +4 more
core +4 more sources
Diffsound: Discrete Diffusion Model for Text-to-Sound Generation [PDF]
IEEE/ACM Transactions on Audio Speech and Language Processing, 2022 Generating sound effects that people want is an important topic. However, there are limited studies in this area for sound generation. In this study, we investigate generating sound conditioned on a text prompt and propose a novel text-to-sound ...
Dongchao Yang +6 more
semanticscholar +1 more source
A Survey of Sound Source Localization with Deep Learning Methods [PDF]
Journal of the Acoustical Society of America, 2021 This article is a survey of deep learning methods for single and multiple sound source localization, with a focus on sound source localization in indoor environments, where reverberation and diffuse noise are present.
Pierre-Amaury Grumiaux +3 more
semanticscholar +1 more source
On the Sound Speed in Neutron Stars [PDF]
Astrophysical Journal Letters, 2022 Determining the sound speed c s in compact stars is an important open question with numerous implications on the behavior of matter at large densities and hence on gravitational-wave emission from neutron stars.
Sinan Altiparmak, C. Ecker, L. Rezzolla
semanticscholar +1 more source
FSD50K: An Open Dataset of Human-Labeled Sound Events [PDF]
IEEE/ACM Transactions on Audio Speech and Language Processing, 2020 Most existing datasets for sound event recognition (SER) are relatively small and/or domain-specific, with the exception of AudioSet, based on over 2 M tracks from YouTube videos and encompassing over 500 sound classes.
Eduardo Fonseca +4 more
semanticscholar +1 more source
Exploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data [PDF]
Knowledge Discovery and Data Mining, 2020 Audio signals generated by the human body (e.g., sighs, breathing, heart, digestion, vibration sounds) have routinely been used by clinicians as indicators to diagnose disease or assess disease progression.
Chloë Brown +8 more
semanticscholar +1 more source
A tool for rapid, automated characterization of population epigenomics in plants
Scientific Reports, 2023 Epigenetic variation in plant populations is an important factor in determining phenotype and adaptation to the environment. However, while advances have been made in the molecular and computational methods to analyze the methylation status of a given ...
Jack M. Colicchio +9 more
doaj +1 more source
BMJ Open Quality, 2022 Background Timely lab results are important to clinical decision-making and hospital flow. However, at our institution, unreliable blood sample collection for patients with central venous access jeopardised this outcome and created staff dissatisfaction ...
Michael Koch +9 more
doaj +1 more source
Sound Event Detection: A tutorial [PDF]
IEEE Signal Processing Magazine, 2021 Imagine standing on a street corner in the city. With your eyes closed you can hear and recognize a succession of sounds: cars passing by, people speaking, their footsteps when they walk by, and the continuous falling of rain.
A. Mesaros +3 more
semanticscholar +1 more source
Deep Convolutional Neural Networks and Data Augmentation for Environmental Sound Classification [PDF]
IEEE Signal Processing Letters, 2016 The ability of deep convolutional neural networks (CNNs) to learn discriminative spectro-temporal patterns makes them well suited to environmental sound classification.
J. Salamon, J. Bello
semanticscholar +1 more source