no code implementations • 27 Jan 2022 • Jivnesh Sandhan, Laxmidhar Behera, Pawan Goyal
On the other hand, purely data-driven approaches do not match the performance of hybrid approaches due to the labelled data sparsity.
1 code implementation • 27 Jan 2022 • Jivnesh Sandhan, Ayush Daksh, Om Adideva Paranjay, Laxmidhar Behera, Pawan Goyal
Nowadays, code-mixing has become ubiquitous in Natural Language Processing (NLP); however, no efforts have been made to address this phenomenon for Speech Translation (ST) task.
1 code implementation • 1 Apr 2021 • Jivnesh Sandhan, Om Adideva, Digumarthi Komal, Laxmidhar Behera, Pawan Goyal
To effectively use such readily available resources, it is very much essential to perform a systematic study on word embedding approaches for the Sanskrit language.
1 code implementation • EACL 2021 • Jivnesh Sandhan, Amrith Krishna, Ashim Gupta, Laxmidhar Behera, Pawan Goyal
In this work, we focus on dependency parsing for morphological rich languages (MRLs) in a low-resource setting.
no code implementations • 16 Jan 2021 • Ashish Kumar, Laxmidhar Behera
The primary motivation behind this work is the limitation of the traditional loss functions for unsupervised learning of a given task.
no code implementations • 11 Oct 2020 • Anima Majumder, Samrat Dutta, Swagat Kumar, Laxmidhar Behera
This is achieved by finding \emph{no man's land} based on Euclidean distance between the feature vectors.
no code implementations • 9 Jan 2020 • Siddhartha Vibhu Pharswan, Mohit Vohra, Ashish Kumar, Laxmidhar Behera
In this paper, we present a novel unsupervised learning based algorithm for the selection of feasible grasp regions.
no code implementations • 3 Jan 2020 • Mohit Vohra, Ravi Prakash, Laxmidhar Behera
In this paper, a real-time grasp pose estimation strategy for novel objects in robotic pick and place applications is proposed.
Robotics Image and Video Processing
no code implementations • 27 Apr 2015 • Vipul Arora, Laxmidhar Behera, Ajay Pratap Yadav
It is hoped that the proposed algorithm will bring in a lot of interest in researchers working in developing fast learning algorithms and global optimization.