OpenL3: Open-source deep audio and image embeddings

A library for soundscape synthesis and augmentation

DCASE2020 Challenge Task 2 baseline system

Sound event detection with depthwise separable and dilated convolutions.

Audio captioning baseline system for DCASE 2020 challenge.

Autoencoder-based baseline system for DCASE2021 Challenge Task 2.

MobileNetV2-based baseline system for DCASE2021 Challenge Task 2.

Unsupervised Domain Adaptation for Acoustic Scene Classification with Wasserstein Distance

Code for the paper "Self-Supervised Learning for 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)

Accompanying code for the paper Design Choices for Learning Embeddings from Auxiliary Tasks for Domain Generalization in Anomalous Sound 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.

Codes related to DCASE2021 Task 1 - Acoustic Scene Classification

Code for using with the Clotho dataset

Codes related to acoustic scene classification task for DCASE 2022

Capstone Project

Accompanying code for the paper On Using Pre-Trained Embeddings for Detecting Anomalous Sounds with Limited Training Data.

Implementation of the threshold-independent performance measure F1-EV for semi-supervised anomaly detection.

Identify a wide variety of bird vocalizations in soundscape recordings

Harmony and Timbre-Oriented MIR Framework