6 accepted papers
In this paper, we propose a collaborative centralized 3D mapping and localization framework that harnesses the capabilities of both SLAM (Simultaneous Localization And Mapping) and XR (eXtended Reality). On one hand, our framework allows for integrating local maps generated by a multitude of heterog
Deep neural network based deepfake detection systems have achieved high levels of accuracy on benchmark datasets and competitions. However, most models lack interpretability. It is challenging to extract reasoning from the network that can convince the human evaluator to trust the decision. Humans o…
Simultaneous Localization and Mapping (SLAM) has emerged as a prime autonomous mobile agent localization algorithm. Despite the global research effort to improve SLAM, its mapping component remains limited and serves little more than to satisfy the coupled localization problem. We present a collabor…
Age estimation from speech is becoming important with increasing usage of the voice channel. Call centers can use age estimates to influence call routing or to provide security by comparison with the speaker's age on-file. Voice assistants can use it for parental control applications. The problem of…
The accuracy of automatic speaker verification (ASV) systems has shown tremendous improvements due to the recent breakthroughs in low-rank speaker representations and deep learning techniques, leading to the success of ASV in real-world applications from call centers to mobile applications and smart…
End-to-end (E2E) Automatic Speech Recognition (ASR) systems are widely applied in various devices and communication domains. However, state-of-the-art ASR systems are known to underperform when there is a mismatch in the training and test domains. As a result, acoustic models deployed in production…