54 citations · 190 across the 11 of their papers we have counts for
5 papers · 1 filter
Low-rank and Sparse Soft Targets to Learn Better DNN Acoustic Models
Pranay Dighe, Afsaneh Asaei, Herve Bourlard
Conventional deep neural networks (DNN) for speech acoustic modeling rely on Gaussian mixture models (GMM) and hidden Markov model (HMM) to obtain binary class labels as the target…
Composition of Deep and Spiking Neural Networks for Very Low Bit Rate Speech Coding
Milos Cernak, Alexandros Lazaridis, Afsaneh Asaei +1
Most current very low bit rate (VLBR) speech coding systems use hidden Markov model (HMM) based speech recognition/synthesis techniques. This allows transmission of information (su…
Exploiting Low-dimensional Structures to Enhance DNN Based Acoustic Modeling in Speech Recognition
Pranay Dighe, Gil Luyet, Afsaneh Asaei +1
We propose to model the acoustic space of deep neural network (DNN) class-conditional posterior probabilities as a union of low-dimensional subspaces. To that end, the training pos…
On Structured Sparsity of Phonological Posteriors for Linguistic Parsing
Milos Cernak, Afsaneh Asaei, Hervé Bourlard
The speech signal conveys information on different time scales from short time scale or segmental, associated to phonological and phonetic information to long time scale or supra s…
TDOA Matrices: Algebraic Properties and their Application to Robust Denoising with Missing Data
Jose Velasco, Daniel Pizarro, Javier Macias-Guarasa +1
Measuring the Time delay of Arrival (TDOA) between a set of sensors is the basic setup for many applications, such as localization or signal beamforming. This paper presents the se…