1 citations · 1 across the 4 of their papers we have counts for
4 papers
ML-SUPERB 2.0: Benchmarking Multilingual Speech Models Across Modeling Constraints, Languages, and Datasets
Jiatong Shi, Shih-Heng Wang, William Chen +8
ML-SUPERB evaluates self-supervised learning (SSL) models on the tasks of language identification and automatic speech recognition (ASR). This benchmark treats the models as featur…
Visual Information Matters for ASR Error Correction
Vanya Bannihatti Kumar, Shanbo Cheng, Ningxin Peng +1
Aiming to improve the Automatic Speech Recognition (ASR) outputs with a post-processing step, ASR error correction (EC) techniques have been widely developed due to their efficienc…
Evaluation of large-scale synthetic data for Grammar Error Correction
Vanya Bannihatti Kumar
Grammar Error Correction(GEC) mainly relies on the availability of high quality of large amount of synthetic parallel data of grammatically correct and erroneous sentence pairs. Th…
Towards Automated Evaluation of Explanations in Graph Neural Networks
Vanya BK, Balaji Ganesan, Aniket Saxena +2
Explaining Graph Neural Networks predictions to end users of AI applications in easily understandable terms remains an unsolved problem. In particular, we do not have well develope…