DEEP NEURAL NET BASED FILTER PREDICTION FOR AUDIO EVENT CLASSIFICATION AND EXTRACTION

摘要

Disclosed is a feature extraction and classification methodology wherein audio data is gathered in a target environment under varying conditions. From this collected data, corresponding features are extracted, labeled with appropriate filters (e.g., audio event descriptions), and used for training deep neural networks (DNNs) to extract underlying target audio events from unlabeled training data. Once trained, these DNNs are used to predict underlying events in noisy audio to extract therefrom features that enable the separation of the underlying audio events from the noisy components thereof.

主权项

1. A method for feature extraction and classification of audio signals using deep neural network based filter prediction, the method comprising:
collecting audio event data under varying conditions; extracting features from the collected audio event data; labeling the extracted features with filter information; and training a deep neural network to perform filter gain prediction using the extracted features.