2 citations · 3 across the 7 of their papers we have counts for
11 papers
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…
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…
Two-Stage Augmentation and Adaptive CTC Fusion for Improved Robustness of Multi-Stream End-to-End ASR
Ruizhi Li, Gregory Sell, Hynek Hermansky
Performance degradation of an Automatic Speech Recognition (ASR) system is commonly observed when the test acoustic condition is different from training. Hence, it is essential to…
A practical two-stage training strategy for multi-stream end-to-end speech recognition
Ruizhi Li, Gregory Sell, Xiaofei Wang +2
The multi-stream paradigm of audio processing, in which several sources are simultaneously considered, has been an active research area for information fusion. Our previous study o…
Multi-Stream End-to-End Speech Recognition
Ruizhi Li, Xiaofei Wang, Sri Harish Mallidi +3
Attention-based methods and Connectionist Temporal Classification (CTC) network have been promising research directions for end-to-end (E2E) Automatic Speech Recognition (ASR). The…