activity
20242026
collaborators

10 papers

eess.AS2026

Enhancing ASR Performance in the Medical Domain for Dravidian Languages

Sri Charan Devarakonda, Ravi Sastry Kolluru, Manjula Sri Rayudu +3

Automatic Speech Recognition (ASR) for low-resource Dravidian languages like Telugu and Kannada faces significant challenges in specialized medical domains due to limited annotated…

cs.CV2026

Using Deep Learning to Generate Semantically Correct Hindi Captions

Wasim Akram Khan, Anil Kumar Vuppala

Automated image captioning using the content from the image is very appealing when done by harnessing the capability of computer vision and natural language processing. Extensive r…

cs.CL2025

Efficient ASR for Low-Resource Languages: Leveraging Cross-Lingual Unlabeled Data

Srihari Bandarupalli, Bhavana Akkiraju, Charan Devarakonda +2

Automatic speech recognition for low-resource languages remains fundamentally constrained by the scarcity of labeled data and computational resources required by state-of-the-art m…

cs.CL2025

TeluguST-46: A Benchmark Corpus and Comprehensive Evaluation for Telugu-English Speech Translation

Bhavana Akkiraju, Srihari Bandarupalli, Swathi Sambangi +3

Despite Telugu being spoken by over 80 million people, speech translation research for this morphologically rich language remains severely underexplored. We address this gap by dev…

eess.AS2025

Fairness in Dysarthric Speech Synthesis: Understanding Intrinsic Bias in Dysarthric Speech Cloning using F5-TTS

M Anuprabha, Krishna Gurugubelli, Anil Kumar Vuppala

Dysarthric speech poses significant challenges in developing assistive technologies, primarily due to the limited availability of data. Recent advances in neural speech synthesis,…

cs.CL2025

End-to-End Speech Translation for Low-Resource Languages Using Weakly Labeled Data

Aishwarya Pothula, Bhavana Akkiraju, Srihari Bandarupalli +3

The scarcity of high-quality annotated data presents a significant challenge in developing effective end-to-end speech-to-text translation (ST) systems, particularly for low-resour…