no code implementations • 1 Jan 2021 • Amber Nigam, Shikha Tyagi, Kuldeep Tyagi, Arpan Saxena
We also propose a BERT-based model, SkillBERT, the embeddings of which are used as features for classifying skills present in the ERRs into groups referred to as "competency groups".
no code implementations • 6 Oct 2019 • Amber Nigam, Pragati Jaiswal, Uma Girkar, Teertha Arora, Leo A. Celi
In this paper, we have discussed initial findings and results of our experiment to predict sexual and reproductive health vulnerabilities of migrants in a data-constrained environment.
no code implementations • 28 May 2019 • Amber Nigam, Aakash Roy, Arpan Saxena, Hartaran Singh
For recommending jobs through machine learning that forms a significant part of our recommendation, we achieve the best results through Bi-LSTM with attention.
no code implementations • 27 Dec 2018 • Amber Nigam, Prashik Sahare, Kushagra Pandya
In this paper, we introduce a methodology for predicting intent and slots of a query for a chatbot that answers career-related queries.
no code implementations • 23 Aug 2018 • Amber Nigam, Arpan Saxena, Ishan Sodhi
In this paper, we have introduced and evaluated intonation based feature for scoring the English speech of nonnative English speakers in Indian context.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 11 Jun 2017 • Amber Nigam
However, lack of appropriate methodology for rating nonnative English speakers' essays has meant a lopsided advancement in this field.