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Showing 1 to 4 of 4 for “"environmental sound classification"”.

  1. Single and Multi-Label Environmental Sound Classification Using Convolutional Neural Networks

    … However, there is a dearth of research on environmental sound analysis. In combination with IoT and wireless sensor networks, artificial neural networks could help to characterize and therefore better address noise issues present in urban environments. This master thesis investigates the …

    chalmers Repository record for Single and Multi-Label Environmental Sound Classification Using Convolutional Neural Networks (opens in a new tab)

  2. AudioCNN: Audio Event Classification With Deep Learning Based Multi-Channel Fusion Networks

    In recent years, there is growing interest in environmental sound classification with a plethora of real-world applications, especially in audio fields like speech and music. Recent research works have proven spectral images based on deep learning models for better performance than standard …

    umkc Repository record for AudioCNN: Audio Event Classification With Deep Learning Based Multi-Channel Fusion Networks (opens in a new tab)

  3. Data-Centric Machine Learning for Speech and Audio

    … demonstrate how data valuation can be used for environmental sound classification. In the context of ecoacoustic monitoring of large data with limited labels, we estimate Shapley values of audio clips with overlapping sounds for a multi-label classifier. We demonstrate that these values identify …

    cuny-grad Repository record for Data-Centric Machine Learning for Speech and Audio (opens in a new tab)

  4. Optimal feature selection and machine learning for high-level audio classification : a random forests approach

    … metadata, and semantics can be extracted from soundtracks of multimedia files. Speech recognition, music information retrieval and environmental sound detection techniques have been developed into a fairly mature technology enabling a final text mining process to obtain semantics for the audio …

    salford Repository record for Optimal feature selection and machine learning for high-level audio classification : a random forests approach (opens in a new tab)