NLP BASED INTERVIEW ASSESSMENT SYSTEM
Mr. Jay Patel, Ms. Disha Sakre, Mr. Dheeraj Purohit, Prof. Dnyaneshwar Bhabad , "NLP BASED INTERVIEW ASSESSMENT SYSTEM", VIVA-IJRI Volume 1, Issue 4, Article 104, pp. 1-6, 2021. Published by Computer Engineering Department, VIVA Institute of Technology, Virar, India.
Online interview is not a new thing but in this covid-19 situation it seems to be the only option. However, assessing the candidate on a video call may not be that effective. Having an AI based Interview Assessment System could prove to be useful, which would take input as speech and will give output as detailed analysis of that speech. While most the research work currently done focuses only on finding sentiment or personality from speech, our system aims to extract multiple information from the speech and provide a detailed analysis. The analysis would include a detailed report containing results about confidence level of the person, his/her emotional state, speed of the speech, frequently repeated words and also personality reflected by that speech. An interview panel consists of various members focusing on different aspect of the answer given by the candidate, some focus on technical correctness while, some simply want to check the communication skills of the candidate. Having an AI system giving a report on the soft skills part would reduce the work for interviewer and he/she could give complete focus on the technical correctness of the answer. This could eventually help save time and resources used by organizations for hiring process. This intention of creating this system is to assist the interview process and give analysis report based on the speech input instead a giving a verdict about selection of the candidate. Thus, this system could use not only by the interviewers but also by the candidates. The output provided would be a detailed report which could prove to be a good feedback for the students who are preparing for the interview. Having a feedback would help candidates work on their week points and thus perform better in further interviews.
natural language processing, neural network, personality detection, regression model, speech signal.
- Li, Wei, et al. "User reviews: Sentiment analysis using lexicon integrated two-channel CNN–LSTM family models." Applied Soft Computing 94 (2020): 106435.
- Mehta, Yash, et al. "Bottom-up and top-down: Predicting personality with psycholinguistic and language model features." 2020 IEEE International Conference on Data Mining (ICDM). IEEE, 2020.
- Akhtar, Md Shad, Asif Ekbal, and Erik Cambria. "How intense are you? Predicting intensities of emotions and sentiments using stacked ensemble [application notes]." IEEE Computational Intelligence Magazine 15.1 (2020): 64-75.
- Go, Alec, Richa Bhayani, and Lei Huang. "Twitter sentiment classification using distant supervision." CS224N project report, Stanford 1.12 (2009): 2009..
- Young, Tom, et al. "Dialogue systems with audio context." Neurocomputing 388 (2020): 102-109.
- Su, Ming-Hsiang, et al. "Personality trait perception from speech signals using multiresolution analysis and convolutional neural networks." 2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC). IEEE, 2017.
- Polzehl, Tim, Sebastian Möller, and Florian Metze. "Automatically assessing acoustic manifestations of personality in speech." 2010 IEEE Spoken Language Technology Workshop. IEEE, 2010.
- Cambria, Erik, et al. "Sentiment analysis is a big suitcase." IEEE Intelligent Systems 32.6 (2017): 74-80.
- Majumder, Navonil, et al. "Dialoguernn: An attentive rnn for emotion detection in conversations." Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 33. No. 01. 2019.
- Jayaratne, Madhura, and Buddhi Jayatilleke. "Predicting personality using answers to open-ended interview questions." IEEE Access 8 (2020): 115345-115355.
- Pramodh, Kasula Chaithanya, and Y. Vijayalata. "Automatic personality recognition of authors using big five factor model." 2016 IEEE International Conference on Advances in Computer Applications (ICACA). IEEE, 2016.
- Rahman, Md Abdur, et al. "Personality Detection from Text using Convolutional Neural Network." 2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT). IEEE, 2019.
- Parmar, Manojkumar, et al. "Sentiment analysis on interview transcripts: An application of NLP for quantitative analysis." 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, 2018.
- Yuan, Cuixin, et al. "Personality recognition based on user generated content." 2018 15th International Conference on Service Systems and Service Management (ICSSSM). IEEE, 2018..
- Chaturvedi, Iti, et al. "Distinguishing between facts and opinions for sentiment analysis: Survey and challenges." Information Fusion 44 (2018): 65-77.