Abusive content detection in the spoken text can be addressed by performing Automatic Speech Recognition (ASR) and leveraging advancements in natural language processing. However, ASR models introduce latency and often ...

This thesis work focuses on advancements in neural style transfer, a process that enables the blending of content and style features to generate stylized images. It explores feature extraction using two encoders: a VGG19-based ...

Modeling directly raw waveforms through neural networks for speech processing is gaining more and more attention. Despite its varied success, a question that remains is: what kind of information are such neural networks ...

This thesis introduces a novel framework for language translation, transitioning from conventional text-based mapping to a phoneme-level modeling approach. By employing articulatory phoneme representations and sparse binary ...