Studying the Effect of Face Masks in Identifying Speakers using LSTM

Mohamed Bader, Ismail Shahin, Abdelfatah Ahmed, Naoufel Werghi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

During the COVID-19 pandemic, it has been a standard procedure for people all around the world to use Respiratory Protection Masks (RPM) that cover both the nose and the mouth. The Consequences of wearing RPMs, those pertaining to the perception and production of spoken communication, are rapidly becoming more prominent. Nevertheless, the utilization of face masks also causes attenuation in voice signals, and this alteration affects speech-processing technologies such as Automatic Speaker Verification (ASV) and speech-to-text conversion. An intervention by a deep learning-based algorithm is considered vital to remedy the issue of inappropriate exploitation of speaker-based technology. Therefore, in the proposed framework, a speaker identification system has been implemented to examine the effect of masks. First, the speech signals have been captured, pre-processed, and augmented by a variety of data augmentation techniques. Afterward, different 'Mel-Frequency Cepstral Coefficients' (MFCC) features have been extracted to be fed into a 'Long Short-Term Memory' (LSTM) for identifying speakers. The system's overall performance has been assessed using accuracy, precision, recall, and Fl-score, which yields 93%, 93.3%, 92.2%, and 92.8%, respectively. The obtained results are still in a rudimentary phase, and they are subjected to further enhancements in the future by data expansion and exploitation of multiple optimization techniques.

Original languageBritish English
Title of host publication2022 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages99-102
Number of pages4
ISBN (Electronic)9781665456005
DOIs
StatePublished - 2022
Event2022 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2022 - Ras Al Khaimah, United Arab Emirates
Duration: 23 Nov 202225 Nov 2022

Publication series

Name2022 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2022

Conference

Conference2022 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2022
Country/TerritoryUnited Arab Emirates
CityRas Al Khaimah
Period23/11/2225/11/22

Keywords

  • COVID-19
  • Deep Learning
  • Face Masks
  • Speaker Identification

Fingerprint

Dive into the research topics of 'Studying the Effect of Face Masks in Identifying Speakers using LSTM'. Together they form a unique fingerprint.

Cite this