TY - GEN
T1 - Polyphonic sound event detection using transposed convolutional recurrent neural network
AU - Chatterjee, Chandra Churh
AU - Mulimani, Manjunath
AU - Koolagudi, Shashidhar G.
N1 - Publisher Copyright:
© 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.
PY - 2020/5
Y1 - 2020/5
N2 - In this paper we propose a Transposed Convolutional Recurrent Neural Network (TCRNN) architecture for polyphonic sound event recognition. Transposed convolution layer, which caries out a regular convolution operation but reverts the spatial transformation and it is combined with a bidirectional Recurrent Neural Network (RNN) to get TCRNN. Instead of the traditional mel spectrogram features, the proposed methodology incorporates mel-IFgram (Instantaneous Frequency spectrogram) features. The performance of the proposed approach is evaluated on sound events of publicly available TUT-SED 2016 and Joint sound scene and polyphonic sound event recognition datasets. Results show that the proposed approach outperforms state-of-the-art methods.
AB - In this paper we propose a Transposed Convolutional Recurrent Neural Network (TCRNN) architecture for polyphonic sound event recognition. Transposed convolution layer, which caries out a regular convolution operation but reverts the spatial transformation and it is combined with a bidirectional Recurrent Neural Network (RNN) to get TCRNN. Instead of the traditional mel spectrogram features, the proposed methodology incorporates mel-IFgram (Instantaneous Frequency spectrogram) features. The performance of the proposed approach is evaluated on sound events of publicly available TUT-SED 2016 and Joint sound scene and polyphonic sound event recognition datasets. Results show that the proposed approach outperforms state-of-the-art methods.
UR - https://www.scopus.com/pages/publications/85091287180
UR - https://www.scopus.com/pages/publications/85091287180#tab=citedBy
U2 - 10.1109/ICASSP40776.2020.9054628
DO - 10.1109/ICASSP40776.2020.9054628
M3 - Conference contribution
AN - SCOPUS:85091287180
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 661
EP - 665
BT - 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020
Y2 - 4 May 2020 through 8 May 2020
ER -