Amanote Research

Amanote Research

    RegisterSign In

A Performance Evaluation of Several Deep Neural Networks for Reverberant Speech Separation

doi 10.1109/acssc.2018.8645219
Full Text
Open PDF
Abstract

Available in full text

Date

October 1, 2018

Authors
Qingju LiuWenwu WangPhilip J.B. JacksonSaeid Safavi
Publisher

IEEE


Related search

Performance Evaluation of Deep Neural Networks Applied to Speech Recognition: RNN, LSTM and GRU

Journal of Artificial Intelligence and Soft Computing Research
Information SystemsPattern RecognitionSimulationHardwareComputer VisionArchitectureModelingArtificial Intelligence
2019English

A Feature Study for Masking-Based Reverberant Speech Separation

2016English

Automatic Speech Recognition With Deep Neural Networks for Impaired Speech

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2016English

Recurrent Timing Neural Networks for Joint F0-Localisation Based Speech Separation

2007English

Genetic Algorithm for Combined Speaker and Speech Recognition Using Deep Neural Networks

Journal of Telecommunications and Information Technology
Electronic EngineeringCommunicationsElectricalComputer Networks
2018English

PhaseNet: Discretized Phase Modeling With Deep Neural Networks for Audio Source Separation

2018English

Interpretable Objective Assessment of Dysarthric Speech Based on Deep Neural Networks

2017English

Binaural Speech Separation Using Recurrent Timing Neural Networks for Joint F0-Localisation Estimation

English

Neural Network Front-Ends Based Speech Recognition in Reverberant Environments

2016English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2025 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy