1. Multitaper mel-spectrograms for keyword spotting
- Author
-
de Souza, Douglas Baptista, Bakri, Khaled Jamal, Ferreira, Fernanda, and Inacio, Juliana
- Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing ,Computer Science - Machine Learning - Abstract
Keyword spotting (KWS) is one of the speech recognition tasks most sensitive to the quality of the feature representation. However, the research on KWS has traditionally focused on new model topologies, putting little emphasis on other aspects like feature extraction. This paper investigates the use of the multitaper technique to create improved features for KWS. The experimental study is carried out for different test scenarios, windows and parameters, datasets, and neural networks commonly used in embedded KWS applications. Experiment results confirm the advantages of using the proposed improved features.
- Published
- 2024