Sound event early detection
AssigneeNEC Corporation
InventorsXuchao Zhang, Yuncong Chen, Haifeng Chen, Wenchao Yu, Wei Cheng, Xujiang Zhao
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Abstract
Systems and methods for Evidence-based Sound Event Early Detection is provided. The system/method includes parsing collected labeled audio corpus data and real time audio streaming data utilizing mel-spectrogram, encoding features of the parsed mel-spectrograms using a trained neural network, and generating a final predicted result for a sound event based on the belief, disbelief and uncertainty outputs from the encoded mel-spectrograms.
Claims20
A computer implemented method for Evidence-based Sound Event Early Detection, comprising:
- parsing overlapping polyphony sound from collected labeled audio corpus data and real-time audio streaming data into spectrogram features utilizing a mel-spectrogram;
- extracting parsed mel-spectrograms with zero-padded frames from the collected labeled audio corpus data and real-time audio streaming data and the spectrogram features;
- encoding features of the parsed mel-spectrograms using a trained neural network to obtain encoded mel-spectrograms;
- and
- detecting sound events from the overlapping polyphony sound by generating a final predicted result for the sound events with a trained neural network that reduces sound event detection delay by utilizing subjective logic with a vacuity threshold and an uncertainty calibration loss based on sums of evidential uncertainty determined based on prediction samples with corresponding strengths of binomial opinion based on belief, disbelief and uncertainty outputs from the encoded mel-spectrograms.
A computer system for Evidence-based Sound Event Early Detection, comprising:
- one or more processors;
- a display screen coupled to the one or more processors through a bus;
- and
- memory coupled to the one or more processors through the bus, wherein the memory includes:
- an audio processing tool that parses overlapping polyphony sound from collected labeled audio corpus data and real-time audio streaming data into spectrogram features by utilizing a mel-spectrogram and extracts parsed mel-spectrograms with zero-padded frames from the collected labeled audio corpus data and real time audio streaming data and the spectrogram features,
- an audio encoding tool that encodes features of the parsed mel-spectrograms using a trained neural network to obtain encoded mel-spectrograms, and
- a sound detection tool that detects sound events from the overlapping polyphony sound and generates a final predicted result for the sound events with the trained neural network that reduces sound event detection delay by utilizing subjective logic with a vacuity threshold and an uncertainty calibration loss based on sums of evidential uncertainty determined based on prediction samples with corresponding strengths of binomial opinion based on the belief, disbelief and uncertainty outputs from the encoded mel-spectrograms.
Dependencies are inferred from the claim text.