Towards Advanced Speech Signal Processing: A Statistical Perspective on Convolution-Based Architectures and its Applications
Year: 2024
Type: preprint
Abstract: This article surveys convolution-based models including convolutional neural networks (CNNs), Conformers, ResNets, and CRNNs-as speech signal processing models and provide their statistical backgrounds and speech recognition, speaker identification, emotion recognition, and speech enhancement applications. Through comparative training cost assessment, model size, accuracy and speed assessment, we compare the strengths and weaknesses of each model, identify potential errors and propose avenues for further research, emphasizing the central role it plays in advancing applications of speech technologies.
Source: arXiv (Cornell University)
Authors: Kapu, Nirmal Joshua, Karan, Raghav
Institution: Indian Institute of Technology Kanpur
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6891936021
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