Arindam Chatterjee


Towards Explainable Dialogue System: Explaining Intent Classification using Saliency Techniques
Ratnesh Joshi | Arindam Chatterjee | Asif Ekbal
Proceedings of the 18th International Conference on Natural Language Processing (ICON)

Deep learning based methods have shown tremendous success in several Natural Language Processing (NLP) tasks. The recent trends in the usage of Deep Learning based models for natural language tasks have definitely produced incredible performance for several application areas. However, one major problem that most of these models face is the lack of transparency, i.e. the actual decision process of the underlying model is not explainable. In this paper, at first we solve a very fundamental problem of Natural Language Understanding (NLU), i.e. intent detection using a Bi-directional Long Short Term Memory (BiLSTM). In order to determine the defining features that lead to a specific intent class, we use the Layerwise Relevance Propagation (LRP) algorithm to find the defining feature(s). In the process, we conclude that saliency method of eLRP (epsilon Layerwise Relevance Propagation) is a prominent process for highlighting the important features of the input responsible for the current classification which results in significant insights to the inner workings, such as the reasons for misclassification by the black box model.


Eating Your Own Cooking: Automatically Linking Wordnet Synsets of Two Languages
Salil Joshi | Arindam Chatterjee | Arun Karthikeyan Karra | Pushpak Bhattacharyya
Proceedings of COLING 2012: Demonstration Papers

Discrimination-Net for Hindi
Diptesh Kanojia | Arindam Chatterjee | Salil Joshi | Pushpak Bhattacharyya
Proceedings of COLING 2012: Demonstration Papers


Together We Can: Bilingual Bootstrapping for WSD
Mitesh M. Khapra | Salil Joshi | Arindam Chatterjee | Pushpak Bhattacharyya
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies