Srikanth Madikeri got his Ph.D. in Computer Science and Engineering from Indian Institute of Technology Madras (India) in 2013. During his Ph.D., he worked on automatic speaker recognition and spoken keyword spotting. He is currently working as a Research Associate at Idiap Research Institute (Martigny, Switzerland) in the Speech Processing group. His current research interests include – Automatic Speech Recognition for low resource languages, Automatic Speaker Recognition and Speaker Diarization.
Automatic Speech Recognition for Low-Resource languages
This talk focuses on automatic speech recognition (ASR) systems for low-resource languages with applications to information retrieval.
A common approach to improve ASR system performance for low-resource ASR is to train multilingual acoustic models by pooling resources from multiple languages. In this talk, we present the challenges and benefits of different multilingual modeling with Lattice-Free Maximum Mutual Information (LF-MMI), the state-of-the-art technique for hybrid ASR systems. We also present an incremental semi-supervised learning approach applied to multi-genre speech recognition, a common task in the MATERIAL program. The simple approach helps avoid fast saturation of performance improvements when using large amounts of data for semi-supervised learning. Finally, we present Pkwrap, a Pytorch wrapper on Kaldi (among the most popular speech recognition toolkits), that helps combine the benefits of training acoustic models with Pytorch and Kaldi. The toolkit, now available at https://github.com/idiap/pkwrap, is intended to provide both fast prototyping benefits of Pytorch while using necessary functionalities from Kaldi (LF-MMI, parallel training, decoding, etc.).
The talk will take place on Monday March 8th 2021 at 13:00 CET, virtually on zoom https://cesnet.zoom.us/j/98589068121.
Amit Kumar Mishra
Amit Kumar Mishra is, currently, a Professor in the Radar Remote Sensing Group at the University of Cape Town. Prof. Mishra has more than 15 years of experience in the domain of radar and radio system design and applied machine learning. His current interests are around the use of cognitive architectures and advanced signal processing and machine learning to understand radar signals. His H-index (Scopus) is 12. He is also a serial innovator and has six patents to his credit.
Fusing Radar and Telecommunication
Radar and telecommunication systems, even though similar in most of their subsystems, need a substantially different set of algorithms and design to make them work. Multiple reasons have been driving more and more researchers to work on possible ways to make radar and telecommunication systems co-exist, cooperate and if possible to co-design of a hybrid system. In this talk, the author shall discuss some of his research-work around fusing telecommunication and radar systems. The talk shall cover three major ideas, viz. commensal radar, symbiotic radar and CommSense system.
His talk is POSTPONED.
Torsten Sattler received a PhD in Computer Science from RWTH Aachen University, Germany, in 2014 under the supervision of Prof. Bastian Leibe and Prof. Leif Kobbelt. In December 2013, he joined the Computer Vision and Geometry Group of Prof. Marc Pollefeys at ETH Zurich, Switzerland, where he currently is a senior researcher and Marc Pollefeys’ deputy while Prof. Pollefeys is on leave from ETH. His research interests include (large-scale) image-based localization using Structure-from-Motion point clouds, real-time localization and SLAM on mobile devices and for robotics, 3D mapping, Augmented abd Virtual Reality, machine learning, (multi-view) stereo, image retrieval and efficient spatial verification, camera calibration and pose estimation. His current work focuses on making algorithms for localization and mapping “smarter” by incorporating higher-level scene understanding.
Torsten has worked on dense sensing for self-driving cars as part of the V-Charge project. He is currently involved in enabling semantic SLAM and re-localization for gardening robots (as part of the Trimbot2020 project, a EU Horizon 2020 project where he leads the efforts on a workpackage), research for Google’s Tango project, where he leads CVG’s research efforts, and in work on self-driving cars.
Torsten has organized multiple tutorials and workshops at CVPR and ICCV. He regularly serves as a reviewer for the top-conferences in Computer Vision (CVPR, ECCV, ICCV) and Robotics (IROS, ICRA) and is an area chair for CVPR 2018 and 3DV 2018. His talk takes place in POSTPONED.
Miloslav Druckmüller is a Professor of Applied Mathematics at the Institute of mathematics, Faculty of Mechanical Engineering, Brno University of Technology and the head of the Department of Computer Graphics and Geometry. His main interests are numerical methods of image analysis, digital image processing, computer graphics and complex variable analysis. During the last 10 years he has been cooperating widely with the Institute for Astronomy, University of Hawaii in the field of solar coronal plasma research. He created a large archive of K-corona (photospheric light scattered on free electrons) images and temperature maps based on Fe and Ni ions observing based on data obtained during total solar eclipses during last two decades. Nowadays his research is mainly focused on processing and analysis of data obtained by NASA SDO spacecraft. His talk takes place in POSTPONED.
Kevin Köser is a senior researcher at the GEOMAR Helmholtz Centre for Ocean Research, Kiel. His main research interest lies in novel camera-based measurement techniques for (deep) sea environments and processes (3D underwater vision). These help to study resources, to explore and monitor (deep) sea habitats or to assess hazards, e.g. with respect to gas flux or seafloor dynamics. In the past years Dr. Köser has taught the classes 3D Photography and Computer Vision Lab at the Swiss Federal Institute of Technology (ETH Zurich) and has worked as a senior researcher in ETH’s Computer Vision and Geometry Lab on shape and motion extraction from photos and videos, geolocalization and image registration. POSTPONED.