A consecutive ensemble of four CRNN models, predicting source count, then directions of arrival, then classes, achieves top results on the DCASE 2019 sound event localization and detection task.
We extract chunks (intervals of equal NOAS) of audio where the predicted NOAS equals 1 and we feed it to doa1 network
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.AS 1years
2019 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Sound source detection, localization and classification using consecutive ensemble of CRNN models
A consecutive ensemble of four CRNN models, predicting source count, then directions of arrival, then classes, achieves top results on the DCASE 2019 sound event localization and detection task.