1 citations · 2 across the 5 of their papers we have counts for
4 papers · 1 filter
Self-supervised Learning with Speech Modulation Dropout
Samik Sadhu, Hynek Hermansky
We show that training a multi-headed self-attention-based deep network to predict deleted, information-dense 2-8 Hz speech modulations over a 1.5-second section of a speech utteran…
Blind Signal Dereverberation for Machine Speech Recognition
Samik Sadhu, Hynek Hermansky
We present a method to remove unknown convolutive noise introduced to speech by reverberations of recording environments, utilizing some amount of training speech data from the rev…
Radically Old Way of Computing Spectra: Applications in End-to-End ASR
Samik Sadhu, Hynek Hermansky
We propose a technique to compute spectrograms using Frequency Domain Linear Prediction (FDLP) that uses all-pole models to fit the squared Hilbert envelope of speech in different…
Wav2vec-C: A Self-supervised Model for Speech Representation Learning
Samik Sadhu, Di He, Che-Wei Huang +6
Wav2vec-C introduces a novel representation learning technique combining elements from wav2vec 2.0 and VQ-VAE. Our model learns to reproduce quantized representations from partiall…