ARawNet: A Lightweight Solution for Leveraging Raw Waveforms in Spoof Speech Detection
Author
Abstract
An emerging trend in audio processing is capturing low-level speech representations from raw waveforms. These representations have shown promising results on a variety of tasks, such as speech recognition and speech separation. Compared to handcrafted features, learning speech features via backpropagation can potentially provide the model greater flexibility in how it represents data for different tasks. However, results from empirical studies show that, in some tasks, such as spoof speech detection, handcrafted features still currently outperform learned features.
Year of Publication
2022
Conference Name
2022 26th International Conference on Pattern Recognition (ICPR)
Date Published
08/2022
Publisher
IEEE
Conference Location
Montreal, QC, Canada
ISBN Number
978-1-6654-9062-7
URL
https://ieeexplore.ieee.org/document/9956138
DOI
10.1109/ICPR56361.2022.9956138
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