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Found 6 papers, 1 papers with code
Multi-input Architecture and Disentangled Representation Learning for Multi-dimensional Modeling of Music Similarity
To achieve this, we propose a multi-input deep neural network architecture, which simultaneously processes mel-spectrogram, CENS-chromagram and tempogram in order to extract informative features for the different disentangled musical dimensions: genre, mood, instrument, era, tempo, and key.
Towards Audio Domain Adaptation for Acoustic Scene Classification using Disentanglement Learning
The deployment of machine listening algorithms in real-life applications is often impeded by a domain shift caused for instance by different microphone characteristics.
USM-SED - A Dataset for Polyphonic Sound Event Detection in Urban Sound Monitoring Scenarios
This paper introduces a novel dataset for polyphonic sound event detection in urban sound monitoring use-cases.
IDMT-Traffic: An Open Benchmark Dataset for Acoustic Traffic Monitoring Research
In many urban areas, traffic load and noise pollution are constantly increasing.
DESED-FL and URBAN-FL: Federated Learning Datasets for Sound Event Detection
Research on sound event detection (SED) in environmental settings has seen increased attention in recent years.
A Study on Spoken Language Identification using Deep Neural Networks
In this paper, we investigate a previously proposed algorithm for spoken language identification based on convolutional neural networks and convolutional recurrent neural networks.
