activity
20172019
most citedRole of Intonation in Scoring Spoken English

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2019

Migration through Machine Learning Lens -- Predicting Sexual and Reproductive Health Vulnerability of Young Migrants

Amber Nigam, Pragati Jaiswal, Uma Girkar +2

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 environm…

cs.IR2019

Job Recommendation through Progression of Job Selection

Amber Nigam, Aakash Roy, Arpan Saxena +1

Job recommendation has traditionally been treated as a filter-based match or as a recommendation based on the features of jobs and candidates as discrete entities. In this paper, w…

cs.CL2019

Intent Detection and Slots Prompt in a Closed-Domain Chatbot

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. We take a multi-staged approach where both t…

cs.CL2018★ 1 cited

Role of Intonation in Scoring Spoken English

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. For this, we created an aut…

cs.CL2017

Exploring Automated Essay Scoring for Nonnative English Speakers

Amber Nigam

Automated Essay Scoring (AES) has been quite popular and is being widely used. However, lack of appropriate methodology for rating nonnative English speakers' essays has meant a lo…