15 citations · 24 across the 25 of their papers we have counts for
5 papers · 1 filter
SLICER: Learning universal audio representations using low-resource self-supervised pre-training
Ashish Seth, Sreyan Ghosh, S. Umesh +1
We present a new Self-Supervised Learning (SSL) approach to pre-train encoders on unlabeled audio data that reduces the need for large amounts of labeled data for audio and speech…
MAST: Multiscale Audio Spectrogram Transformers
Sreyan Ghosh, Ashish Seth, S. Umesh +1
We present Multiscale Audio Spectrogram Transformer (MAST) for audio classification, which brings the concept of multiscale feature hierarchies to the Audio Spectrogram Transformer…
Technology Pipeline for Large Scale Cross-Lingual Dubbing of Lecture Videos into Multiple Indian Languages
Anusha Prakash, Arun Kumar, Ashish Seth +24
Cross-lingual dubbing of lecture videos requires the transcription of the original audio, correction and removal of disfluencies, domain term discovery, text-to-text translation in…
Analyzing the factors affecting usefulness of Self-Supervised Pre-trained Representations for Speech Recognition
Ashish Seth, Lodagala V S V Durga Prasad, Sreyan Ghosh +1
Self-supervised learning (SSL) to learn high-level speech representations has been a popular approach to building Automatic Speech Recognition (ASR) systems in low-resource setting…
DeLoRes: Decorrelating Latent Spaces for Low-Resource Audio Representation Learning
Sreyan Ghosh, Ashish Seth, and Deepak Mittal +2
Inspired by the recent progress in self-supervised learning for computer vision, in this paper we introduce DeLoRes, a new general-purpose audio representation learning approach. O…