3 citations · 4 across the 8 of their papers we have counts for
8 papers · 1 filter
Voice of India: A Large-Scale Benchmark for Real-World Speech Recognition in India
Kaushal Bhogale, Manas Dhir, Amritansh Walecha +11
Existing Indic ASR benchmarks often use scripted, clean speech and leaderboard driven evaluation that encourages dataset specific overfitting. In addition, strict single reference…
Towards Orthographically-Informed Evaluation of Speech Recognition Systems for Indian Languages
Kaushal Santosh Bhogale, Tahir Javed, Greeshma Susan John +4
Evaluating ASR systems for Indian languages is challenging due to spelling variations, suffix splitting flexibility, and non-standard spellings in code-mixed words. Traditional Wor…
NIRANTAR: Continual Learning with New Languages and Domains on Real-world Speech Data
Tahir Javed, Kaushal Bhogale, Mitesh M. Khapra
We introduce Nirantar, a comprehensive framework for evaluating continual learning (CL) in multilingual and multi-domain ASR. Designed to reflect real-world CL challenges, Nirantar…
Empowering Low-Resource Language ASR via Large-Scale Pseudo Labeling
Kaushal Santosh Bhogale, Deovrat Mehendale, Niharika Parasa +4
In this study, we tackle the challenge of limited labeled data for low-resource languages in ASR, focusing on Hindi. Specifically, we explore pseudo-labeling, by proposing a generi…
LAHAJA: A Robust Multi-accent Benchmark for Evaluating Hindi ASR Systems
Tahir Javed, Janki Nawale, Sakshi Joshi +4
Hindi, one of the most spoken language of India, exhibits a diverse array of accents due to its usage among individuals from diverse linguistic origins. To enable a robust evaluati…
IndicVoices: Towards building an Inclusive Multilingual Speech Dataset for Indian Languages
Tahir Javed, Janki Atul Nawale, Eldho Ittan George +18
We present INDICVOICES, a dataset of natural and spontaneous speech containing a total of 7348 hours of read (9%), extempore (74%) and conversational (17%) audio from 16237 speaker…