8 papers
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…
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…
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,…
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…
IIITH-BUT system for IWSLT 2025 low-resource Bhojpuri to Hindi speech translation
Bhavana Akkiraju, Aishwarya Pothula, Santosh Kesiraju +1
This paper presents the submission of IIITH-BUT to the IWSLT 2025 shared task on speech translation for the low-resource Bhojpuri-Hindi language pair. We explored the impact of hyp…
A Preliminary Analysis of Automatic Word and Syllable Prominence Detection in Non-Native Speech With Text-to-Speech Prosody Embeddings
Anindita Mondal, Rangavajjala Sankara Bharadwaj, Jhansi Mallela +2
Automatic detection of prominence at the word and syllable-levels is critical for building computer-assisted language learning systems. It has been shown that prosody embeddings le…