Indian English

Indian English, a significant variety of the language spoken by a vast population, is a growing area of linguistic and technological research. Current studies focus on improving the accuracy of automatic speech recognition (ASR) and natural language processing (NLP) models for Indian English accents, often employing deep learning architectures like convolutional neural networks (CNNs) and recurrent neural networks (RNNs), and exploring techniques like transfer learning and data augmentation. This research is crucial for bridging the digital divide and ensuring equitable access to technology, particularly in areas like online safety (detecting gendered abuse) and accessibility for individuals with diverse accents. The development of specialized datasets, such as those for question answering and speech-to-intent tasks, is also a key focus, enabling more robust and accurate model training.