1 citations · 2 across the 6 of their papers we have counts for
8 papers
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…
Stabilized training of joint energy-based models and their practical applications
Martin Sustek, Samik Sadhu, Lukas Burget +4
The recently proposed Joint Energy-based Model (JEM) interprets discriminatively trained classifier as an energy model, which is also trained as a generative model describ…
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…
Importance of Different Temporal Modulations of Speech: A Tale of Two Perspectives
Samik Sadhu, Hynek Hermansky
How important are different temporal speech modulations for speech recognition? We answer this question from two complementary perspectives. Firstly, we quantify the amount of phon…
Complex Frequency Domain Linear Prediction: A Tool to Compute Modulation Spectrum of Speech
Samik Sadhu, Hynek Hermansky
Conventional Frequency Domain Linear Prediction (FDLP) technique models the squared Hilbert envelope of speech with varied degrees of approximation which can be sampled at the requ…
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…
Exploring Methods for the Automatic Detection of Errors in Manual Transcription
Xiaofei Wang, Jinyi Yang, Ruizhi Li +2
Quality of data plays an important role in most deep learning tasks. In the speech community, transcription of speech recording is indispensable. Since the transcription is usually…