Kunal Chakma


2023

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Cross-Lingual Speaker Identification for Indian Languages
Amaan Rizvi | Anupam Jamatia | Dwijen Rudrapal | Kunal Chakma | Björn Gambäck
Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing

The paper introduces a cross-lingual speaker identification system for Indian languages, utilising a Long Short-Term Memory dense neural network (LSTM-DNN). The system was trained on audio recordings in English and evaluated on data from Hindi, Kannada, Malayalam, Tamil, and Telugu, with a view to how factors such as phonetic similarity and native accent affect performance. The model was fed with MFCC (mel-frequency cepstral coefficient) features extracted from the audio file. For comparison, the corresponding mel-spectrogram images were also used as input to a ResNet-50 model, while the raw audio was used to train a Siamese network. The LSTM-DNN model outperformed the other two models as well as two more traditional baseline speaker identification models, showing that deep learning models are superior to probabilistic models for capturing low-level speech features and learning speaker characteristics.

2015

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Sentence Boundary Detection for Social Media Text
Dwijen Rudrapal | Anupam Jamatia | Kunal Chakma | Amitava Das | Björn Gambäck
Proceedings of the 12th International Conference on Natural Language Processing