WaDeNet: Wavelet Decomposition based CNN for Speech Processing

11/11/2020
by   Prithvi Suresh, et al.
0

Existing speech processing systems consist of different modules, individually optimized for a specific task such as acoustic modelling or feature extraction. In addition to not assuring optimality of the system, the disjoint nature of current speech processing systems make them unsuitable for ubiquitous health applications. We propose WaDeNet, an end-to-end model for mobile speech processing. In order to incorporate spectral features, WaDeNet embeds wavelet decomposition of the speech signal within the architecture. This allows WaDeNet to learn from spectral features in an end-to-end manner, thus alleviating the need for feature extraction and successive modules that are currently present in speech processing systems. WaDeNet outperforms the current state of the art in datasets that involve speech for mobile health applications such as non-invasive emotion recognition. WaDeNet achieves an average increase in accuracy of 6.36 Additionally, WaDeNet is considerably lighter than a simple CNNs with a similar architecture.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/01/2022

A Wavelet Transform Based Scheme to Extract Speech Pitch and Formant Frequencies

Pitch and Formant frequencies are important features in speech processin...
research
01/22/2016

Speech vocoding for laboratory phonology

Using phonological speech vocoding, we propose a platform for exploring ...
research
09/18/2020

Optimizing Speech Emotion Recognition using Manta-Ray Based Feature Selection

Emotion recognition from audio signals has been regarded as a challengin...
research
02/23/2018

Do WaveNets Dream of Acoustic Waves?

Various sources have reported the WaveNet deep learning architecture bei...
research
08/15/2022

Towards Parametric Speech Synthesis Using Gaussian-Markov Model of Spectral Envelope and Wavelet-Based Decomposition of F0

Neural network-based Text-to-Speech has significantly improved the quali...
research
01/20/2017

End-To-End Visual Speech Recognition With LSTMs

Traditional visual speech recognition systems consist of two stages, fea...
research
02/11/2021

Language Independent Emotion Quantification using Non linear Modelling of Speech

At present emotion extraction from speech is a very important issue due ...

Please sign up or login with your details

Forgot password? Click here to reset