Survey of deep learning paradigms for speech processing
KB Bhangale, M Kothandaraman - Wireless Personal Communications, 2022 - Springer
Over the past decades, a particular focus is given to research on machine learning
techniques for speech processing applications. However, in the past few years, research …
techniques for speech processing applications. However, in the past few years, research …
An overview of voice conversion systems
SH Mohammadi, A Kain - Speech Communication, 2017 - Elsevier
Voice transformation (VT) aims to change one or more aspects of a speech signal while
preserving linguistic information. A subset of VT, Voice conversion (VC) specifically aims to …
preserving linguistic information. A subset of VT, Voice conversion (VC) specifically aims to …
A unique approach in text independent speaker recognition using MFCC feature sets and probabilistic neural network
KS Ahmad, AS Thosar, JH Nirmal… - … on Advances in Pattern …, 2015 - ieeexplore.ieee.org
This paper motivates the use of combination of mel frequency cepstral coefficients (MFCC)
and its delta derivatives (DMFCC and DDMFCC) calculated using mel spaced Gaussian …
and its delta derivatives (DMFCC and DDMFCC) calculated using mel spaced Gaussian …
[PDF][PDF] Voice Conversion Across Arbitrary Speakers Based on a Single Target-Speaker Utterance.
Developing a voice conversion (VC) system for a particular speaker typically requires
considerable data from both the source and target speakers. This paper aims to effectuate …
considerable data from both the source and target speakers. This paper aims to effectuate …
Speaker identification using vowels features through a combined method of formants, wavelets, and neural network classifiers
K Daqrouq, TA Tutunji - Applied Soft Computing, 2015 - Elsevier
This paper proposes a new method for speaker feature extraction based on Formants,
Wavelet Entropy and Neural Networks denoted as FWENN. In the first stage, five formants …
Wavelet Entropy and Neural Networks denoted as FWENN. In the first stage, five formants …
Modeling of chemical exergy of agricultural biomass using improved general regression neural network
YW Huang, MQ Chen, Y Li, J Guo - Energy, 2016 - Elsevier
A comprehensive evaluation for energy potential contained in agricultural biomass was a
vital step for energy utilization of agricultural biomass. The chemical exergy of typical …
vital step for energy utilization of agricultural biomass. The chemical exergy of typical …
Accurate prediction of chemical exergy of technical lignins for exergy-based assessment on sustainable utilization processes
Y Huang, H Wang, X Zhang, Q Zhang, C Wang, L Ma - Energy, 2022 - Elsevier
The exergy-based assessment on the sustainable utilization processes of technical lignin is
important for potential identify and process optimization. In this study, chemical exergy of …
important for potential identify and process optimization. In this study, chemical exergy of …
Speaker-independent expressive voice synthesis using learning-based hybrid network model
Emotional voice conversion systems are used to formulate mapping functions to transform
the neutral speech from output of text-to-speech systems to that of target emotion …
the neutral speech from output of text-to-speech systems to that of target emotion …
Modified multiple generalized regression neural network models using fuzzy C-means with principal component analysis for noise prediction of offshore platform
A modified multiple generalized regression neural network (GRNN) is proposed to predict
the noise level of various compartments onboard of the offshore platform. With limited …
the noise level of various compartments onboard of the offshore platform. With limited …
An effective parallel integrated neural network system for industrial data prediction
W Cao, C Zhang - Applied Soft Computing, 2021 - Elsevier
Abstract At present, General Regression Neural Network (GRNN) have been more and more
used for data prediction in industry, however, because its smoothing factor is difficult to …
used for data prediction in industry, however, because its smoothing factor is difficult to …