14 accepted papers
Edge caching enhances user experience and network efficiency by locally storing popular content. Using federated learning to find popular content enables model training directly on edge devices, eliminating the need to share raw content request data. However, involving multiple devices in training c…
The rapid advancement of Internet of Things (IoT) technology has improved the connectivity of several applications. The recent introduction of mobile IoT devices (IoTDs) has further broadened the scope of conventional IoT networks, resulting in the Internet of Mobile Things (IoMT). However, the IoTD…
With the advent of federated learning, the development of privacy-preserving learning models has assumed significance in several applications. However, challenges arise due to the participation of a massive number of edge devices and limited resources in a network. In this context, this paper addres…
This paper presents a novel framework for super-resolution direction of arrival (DOA) estimation of acoustic sources in the spherical harmonics (SH) domain. The proposed approach combines sparse Bayesian learning (SBL) with a convolutional neural network (CNN). The CNN is utilized to classify DOA ba…
Lipreading is a difficult task, even for humans. And synthesizing the original speech waveform from lipreading makes it even a more challenging problem. Towards this end, we present a deep learning framework that can be trained end-to-end to learn the mapping between the auditory and visual signals.…
Understanding the relationship between the auditory and visual signals is crucial for many different applications ranging from computer-generated imagery (CGI) and video editing automation to assisting people with hearing or visual impairments. However, this is challenging since the distribution of…
Robotic calibration allows for the fusion of data from multiple sensors such as odometers, cameras, etc., by providing appropriate relationships between the corresponding reference frames. For wheeled robots equipped with camera/lidar along with wheel encoders, calibration entails learning the motio…
Performance of conventional audio equalization methods for improving in-car audio listening experience is limited by the uncertainties in computing the highly varying in-car channel response. Hence these methods generally compute the channel response which is then utilized in designing the inverse f…
Energy-efficient data aggregation is a challenging problem in asynchronous wireless sensor networks. Asynchronous behaviour of sensor nodes is generally due to adaptive duty cycling and it leads to information loss, buffer overflow and poor quality of services. To overcome these issues, a joint mobi…
Frequency and location dependent components in the speech signal can be decoupled by signal processing in the spherical harmonic domain. In this paper, a sparsity based method for joint source localization and separation method using online dictionary learning is proposed. Conventional sparsity base…
Signal processing in spherical harmonic domain has the ability to decouple frequency dependent and location dependent components of the signal received. A method for low dimensional spherical harmonic feature extraction is proposed in this work for DOA estimation in noisy and reverberant environment…
Radial filter design for processing near field speech sources over a spherical microphone array is challenging. Polynomial based radial filter design procedures have been proposed in earlier work. In this paper we address the issue of radial filter design using a family of orthogonal polynomials cal…
Spherical harmonics root-MUSIC (MUltiple SIgnal Classification) technique for source localization using spherical microphone array is presented in this paper. Earlier work on root-MUSIC is limited to linear and planar arrays. Root-MUSIC for planar array utilizes the concept of manifold separation an…
Source localization has been studied in the spatial domain using differential geometry in earlier work. However, parameters of the sensor array manifold have hitherto not been investigated for source localization in spherical harmonics domain. The objective of this work is to represent and model the…