Raghav Karan
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Raghav Karan has a total of 1 co-authors. Here are the top co-authors by number of shared publications:
- Kapu Nirmal Joshua
Indian Institute of Technology, Kanpur, India
2 shared publications
Latest Publications
- Open Access
- 6 January 2025
- Published by MDPI AG in Preprints.org
Towards Advanced Speech Signal Processing: A Statistical Perspective on Convolution-Based Architectures and It’s Applications
This article surveys convolution-based models 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, emphasising the central role it plays in advancing applications of speech technologies.
- 6 January 2025
- Published by MDPI AG in Preprints.org
Open AccessTowards Advanced Speech Signal Processing: A Statistical Perspective on Convolution-Based Architectures and It’s Applications
This article surveys convolution-based models 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, emphasising the central role it plays in advancing applications of speech technologies.
- Open Access
- 18 November 2024
- Published by MDPI AG in Preprints.org
Towards Advanced Speech Signal Processing: A Statistical Perspective on Convolution-Based Architectures and it’s Applications
This article surveys convolution-based models 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, emphasising the central role it plays in advancing applications of speech technologies.
- 18 November 2024
- Published by MDPI AG in Preprints.org
Open AccessTowards Advanced Speech Signal Processing: A Statistical Perspective on Convolution-Based Architectures and it’s Applications
This article surveys convolution-based models 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, emphasising the central role it plays in advancing applications of speech technologies.