The tool provides a one-click interface to train NLP models for various tasks using the data stored in the system and then use it for assistance in further storage of the data (especially for the field linguists).
The paper presents Anlirika’s submission to SIGTYP 2021 Shared Task on Robust Spoken Language Identification.
Since its a web-based application, it also allows for seamless collaboration among multiple persons and sharing the data, models, etc with each other.
If approached as three separate classification tasks, the task includes three sub-tasks: aggression identification (sub-task A), gender bias identification (sub-task B), and communal bias identification (sub-task C).
As state-of-the-art neural networks scale to billions of parameters, designing parallel algorithms that can train these networks efficiently on multi-GPU clusters has become critical.
Mixture-of-Experts (MoE) is a neural network architecture that adds sparsely activated expert blocks to a base model, increasing the number of parameters without impacting computational costs.
In this paper we discuss an in-progress work on the development of a speech corpus for four low-resource Indo-Aryan languages -- Awadhi, Bhojpuri, Braj and Magahi using the field methods of linguistic data collection.
In this paper, we discuss the development of a multilingual dataset annotated with a hierarchical, fine-grained tagset marking different types of aggression and the "context" in which they occur.
This phenomenon has spurred the development of algorithms for distributed training of neural networks over a larger number of hardware accelerators.
This has necessitated the development of efficient algorithms to train these neural networks in parallel on large-scale GPU-based clusters.
Results are performed with ShapeNet as the source domain and domains within the Object Dataset Domain Suite (ODDS) dataset as the target, which is a real world multiview, multidomain image dataset.
Online forums and social media platforms are increasingly being used to discuss topics of varying polarities where different people take different stances.
In this paper, we discuss the development of a multilingual annotated corpus of misogyny and aggression in Indian English, Hindi, and Indian Bangla as part of a project on studying and automatically identifying misogyny and communalism on social media (the ComMA Project).
We show how agents trained with SQLoss evolve cooperative behavior in several social dilemma matrix games.
This leads to a frequent tension in robotic learning: how can we learn generalizable robotic controllers without having to collect impractically large amounts of data for each separate experiment?
no code implementations • 11 Aug 2018 • Tsung-Ting Kuo, Jina Huh, Ji-Hoon Kim, Robert El-Kareh, Siddharth Singh, Stephanie Feudjio Feupe, Vincent Kuri, Gordon Lin, Michele E. Day, Lucila Ohno-Machado, Chun-Nan Hsu
Our study introduces CLEAN (CLinical note rEview and ANnotation), a pre-annotation-based cNLP annotation system to improve clinical note annotation of data elements, and comprehensively compares CLEAN with the widely-used annotation system Brat Rapid Annotation Tool (BRAT).
We present a personalized recommender system using neural network for recommending products, such as eBooks, audio-books, Mobile Apps, Video and Music.