Technical Program

Paper Detail

Paper:SP-P10.12
Session:Topics in Speech Enhancement
Time:Wednesday, May 19, 15:30 - 17:30
Presentation: Poster
Topic: Speech Processing: Speech Enhancement
Title: SPEECH ENHANCEMENT WITH MISSING DATA TECHNIQUES USING RECURRENT NEURAL NETWORKS
Authors: Shahla Parveen; University of Sheffield 
 Phil Green; University of Sheffield 
Abstract: This paper presents an application of missing data techniques in speech enhancement. The enhancement system consists of two stages: the first stage uses a Recurrent Neural Network, which is supplied with noisy speech and produces enhanced speech; whereas the second stage uses missing data techniques to further improve the quality of enhanced speech. The results suggest that combining missing data technique with RNN enhancement is an effective enhancement scheme resulting in a 16 dB background noise reduction for all input signal to noise ratio (SNR) conditions from -5 to 20 dB, improved spectral quality and robust automatic speech recognition performance.
 
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