Hemant Yadav

De-STT: De-entaglement of unwanted Nuisances and Biases in Speech to Text System using Adversarial Forgetting

2020 · arXiv (Cornell University)

Training a robust Speech to Text (STT) system requires tens of thousands of hours of data. Variabilities present in the dataset such as unwanted nuisances (environmental noise, etc) and biases (accent, gender, age, etc) are …

MS-HuBERT: Mitigating Pre-training and Inference Mismatch in Masked Language Modelling methods for learning Speech Representations

2024 · arXiv (Cornell University)

In recent years, self-supervised pre-training methods have gained significant traction in learning high-level information from raw speech. Among these methods, HuBERT has demonstrated SOTA performance in automatic speech recognition (ASR). However, HuBERT's performance lags behind …