Identify a wide variety of bird vocalizations in soundscape recordings
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Updated
Jul 22, 2022 - Jupyter Notebook
Identify a wide variety of bird vocalizations in soundscape recordings
Capstone Project
Harmony and Timbre-Oriented MIR Framework
Code for the paper "AdaProj: Adaptively Scaled Angular Margin Subspace Projections for Anomalous Sound Detection with Auxiliary Classification Tasks"
Implementation of the threshold-independent performance measure F1-EV for semi-supervised anomaly detection.
Deep neural network model combining audio signal processing and pre-trained audio CNN achieved 90.1% adjusted accuracy (27.6% improvement) for classifying audio recording environment.
Code for using with the Clotho dataset
Codes related to acoustic scene classification task for DCASE 2022
Accompanying code for the paper On Using Pre-Trained Embeddings for Detecting Anomalous Sounds with Limited Training Data.
Codes related to DCASE2021 Task 1 - Acoustic Scene Classification
Accompanying code for the paper Design Choices for Learning Embeddings from Auxiliary Tasks for Domain Generalization in Anomalous Sound Detection.
Submission for task 2 "First-Shot Unsupervised Anomalous Sound Detection for Machine Condition Monitoring" of the DCASE challenge 2023 (https://dcase.community/challenge2023/task-first-shot-unsupervised-anomalous-sound-detection-for-machine-condition-monitoring)
Code for the paper "Self-Supervised Learning for Anomalous Sound Detection"
Unsupervised Domain Adaptation for Acoustic Scene Classification with Wasserstein Distance
Sound event detection with depthwise separable and dilated convolutions.
MobileNetV2-based baseline system for DCASE2021 Challenge Task 2.
Autoencoder-based baseline system for DCASE2021 Challenge Task 2.
Audio captioning baseline system for DCASE 2020 challenge.
DCASE2020 Challenge Task 2 baseline system
A library for soundscape synthesis and augmentation
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