Convolutional Recurrent Neural Network-Based #EventDetection in Tunnels Using Multiple #Microphones https://t.co/cAsPtUcJx8 #tunnelaccidentdetection #soundeventdetection #CRNN

Joint Optimization of #DeepNeuralNetwork-Based Dereverberation and Beamforming for #SoundEventDetection in Multi-Channel Environments 👉 https://t.co/ULTRnk664c #jointoptimization #soundeventdetection

#AdaptiveNoiseReduction for Sound Event Detection Using Subband-Weighted NMF @QMUL 👉 https://t.co/UkrbDitJDZ #soundeventdetection #nonstationarynoise #sourceseparation #sensors

9 Reasons Why #SoundEventDetection Fails #naturallanguageprocessing #NLPmodel #videoannotation #annotation #datalabeling #machinelearning #audiolabeling Read why in this article 👉 https://t.co/4EBbecj5Ka

We are glad to share about our recent journal overview article “Sound Event Detection: A Journey Through DCASE Challenge Series” published in APSIPA Transactions on Signal and Information Processing. Article Link: https://t.co/jcfWQxGdOA #SoundEventDetection #DCASE #APSIPA

Acoustic Emission and Artificial Intelligence Procedure for Crack Source Localization https://t.co/A2bj7IvAuc @PoliTOnews @Fuzhou_Uni #AcousticEmission #ArtificialNeuralNetwork #AkaikeInformationCriterion #AIC #SourceLocation #SeismicSignals #CrackLocation #SoundEventDetection

Happy to finally attend @ieeeICASSP! Tomorrow, I will present a poster related to #energyconsumption of #SoundEventDetection systems. Pass by to learn more about it or just say hi 😃 📄 link to paper: https://t.co/ENgDeMHRfJ 👩‍💻 code: https://t.co/TfWFk1mMHL

@sebastienroblin @David_Hambling Proposal: having a low-cost distributed microphone network (e.g. raspberry pi) running SoundEventDetection and detecting the targeted lawn mower sound, can probably provide lower false positives than radar for low-flying slow moving objects.

Sound Event Detection of Weakly Labelled Data with CNN-Transformer and Automatic Threshold Optimization 論文： https://t.co/YYuAoakwzx ���部実装： https://t.co/tbejWxOsVp ・SoundEventDetectionにおいてTransformerを適用した研究 ・clip単位、segment単位の学習が可能 （続く）

Happy to share our new paper on language modelling for sound event detection! Paper on arXiv: https://t.co/ejtf9xOsS1 Code on GitHub: https://t.co/gexuLbWvon #soundevents #PyTorch #audio #soundeventdetection #dsp #signalprocessing #sound

Explore the power of sound with our Sound Event Detection (SED) component! A breakthrough method for detecting active sound events, SED offers detailed insights into your scene. Watch the demo: https://t.co/yS2TXCH3NZ #MARVELProject #SoundEventDetection #EUfunded #H2020

Automatic wheeze segmentation using harmonic-percussive source separation and empirical mode decomposition #TechRxiv #Respiratory #SoundAnalysis #ExpertSystems #EmpiricalModeDecomposition #SoundEventDetection https://t.co/rDjMnXXiBk

Imagimob has developed a #tinyML model for gunshot detection that has been optimised to run on @SynaCorp DBM10L #AI chip #SED #soundeventdetection

One more #puplication has been released as part of the @MARVELprojecteu dissemination activities. In this #paper, we propose novel neural architectures based on #PhiNets for real-time acoustic event detection on microcontroller units. https://t.co/Mgtgckg89B #SoundEventDetection

Happy to share our preprint on a novel #algorithm for #sound event detection that generalizes better and is faster. It is now a #regression task instead of frame-based #classification. @djmoffat @bio_computer #AudioSegmentation #SoundEventDetection