no code implementations • 7 Feb 2024 • Pramit Saha, Divyanshu Mishra, Felix Wagner, Konstantinos Kamnitsas, J. Alison Noble
Secondly, we introduce a modality imputation network (MIN) pre-trained in a multimodal client for modality translation in unimodal clients and investigate its potential towards mitigating the missing modality problem.
no code implementations • 10 Dec 2023 • Hudson Hilal, Pramit Saha
Our experiments revealed that the machine learning algorithms on handcrafted features performed particularly well, resulting in 10-20% average mean absolute percentage error.
no code implementations • 10 Dec 2023 • Chenhao He, Pramit Saha
The utilization of deep learning-based object detection is an effective approach to assist visually impaired individuals in avoiding obstacles.
no code implementations • 1 Nov 2023 • Divyanshu Mishra, He Zhao, Pramit Saha, Aris T. Papageorghiou, J. Alison Noble
To detect OOD samples in this context, the resulting model should generalise to the intra-anatomy variations while rejecting similar OOD samples.
no code implementations • 28 Oct 2023 • Pramit Saha, Divyanshu Mishra, J. Alison Noble
The most challenging, yet practical, setting of semi-supervised federated learning (SSFL) is where a few clients have fully labeled data whereas the other clients have fully unlabeled data.
1 code implementation • 31 Aug 2023 • Felix Wagner, Zeju Li, Pramit Saha, Konstantinos Kamnitsas
This paper challenges this assumption and introduces FedPDA, a novel adaptation framework that brings the utility of learning from remote data from Federated Learning into PDA.
no code implementations • 2 Feb 2021 • Pramit Saha, Debasish Ray Mohapatra, Sidney Fels
Considering the upper palate as fixed and the spline model as the dynamically moving lower surface (tongue) of the vocal tract, we compute 1D area functional values that are fed to the Pink Trombone, generating continuous speech sounds.
no code implementations • 29 Jun 2020 • Pramit Saha, Yadong Liu, Bryan Gick, Sidney Fels
Thousands of individuals need surgical removal of their larynx due to critical diseases every year and therefore, require an alternative form of communication to articulate speech sounds after the loss of their voice box.
no code implementations • 16 May 2020 • Pramit Saha, Sidney Fels
The articulatory geometric configurations of the vocal tract and the acoustic properties of the resultant speech sound are considered to have a strong causal relationship.
no code implementations • 8 Apr 2019 • Pramit Saha, Muhammad Abdul-Mageed, Sidney Fels
Speech-related Brain Computer Interfaces (BCI) aim primarily at finding an alternative vocal communication pathway for people with speaking disabilities.
no code implementations • 8 Apr 2019 • Pramit Saha, Muhammad Abdul-Mageed, Sidney Fels
Speech-related Brain Computer Interface (BCI) technologies provide effective vocal communication strategies for controlling devices through speech commands interpreted from brain signals.
no code implementations • 8 Apr 2019 • Pramit Saha, Sidney Fels
We propose a mixed deep neural network strategy, incorporating parallel combination of Convolutional (CNN) and Recurrent Neural Networks (RNN), cascaded with deep autoencoders and fully connected layers towards automatic identification of imagined speech from EEG.
1 code implementation • 17 Sep 2018 • Amir H. Abdi, Pramit Saha, Praneeth Srungarapu, Sidney Fels
In this article, we propose a deep reinforcement learning method to estimate the muscle excitations in simulated biomechanical systems.
no code implementations • 29 Jul 2018 • Pramit Saha, Praneeth Srungarapu, Sidney Fels
Interestingly, the results show a marked difference in the model performance in the context of speech classification with respect to generic sequence or video classification tasks.