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20212024
most citedBiologically inspired speech emotion recognition

57 citations · 99 across the 5 of their papers we have counts for

collaborators

5 papers

eess.AS2024★ 1 cited

Zero-Bit Transmission of Adaptive Pre- and De-emphasis Filters for Speech and Audio Coding

Niloofar Omidi Piralideh, Philippe Gournay, Roch Lefebvre

This paper introduces a novel adaptation approach for first-order pre- and de-emphasis filters, an essential tool in many speech and audio codecs to increase coding efficiency and…

eess.AS2022

Practical cognitive speech compression

Reza Lotfidereshgi, Philippe Gournay

This paper presents a new neural speech compression method that is practical in the sense that it operates at low bitrate, introduces a low latency, is compatible in computational…

eess.AS2021★ 41 cited

Speech Prediction using an Adaptive Recurrent Neural Network with Application to Packet Loss Concealment

Reza Lotfidereshgi, Philippe Gournay

This paper proposes a novel approach for speech signal prediction based on a recurrent neural network (RNN). Unlike existing RNN-based predictors, which operate on parametric featu…

eess.AS2021★ 57 cited

Biologically inspired speech emotion recognition

Reza Lotfidereshgi, Philippe Gournay

Conventional feature-based classification methods do not apply well to automatic recognition of speech emotions, mostly because the precise set of spectral and prosodic features th…

eess.AS2021

Cognitive Coding of Speech

Reza Lotfidereshgi, Philippe Gournay

We propose an approach for cognitive coding of speech by unsupervised extraction of contextual representations in two hierarchical levels of abstraction. Speech attributes such as…