Speech Disorders Classification in Phonetic Exams with MFCC and DTW

Jueting Liu, Marisha Speights, Dallin Bailey, Sicheng Li, Huanyi Zhou, Yaoxuan Luan, Tianshi Xie, Cheryl Seals

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Recognizing disordered speech is a challenge to Automatic Speech Recognition (ASR) systems. This research focuses on classifying disordered speech vs. non-disordered speech through signal processing coupled with machine learning techniques. We have found little evidence of ASR that correctly classifies disordered vs. ordered speech at the level of expert-based classification. This research supports the Automated Phonetic Transcription - Grading Tool (APTgt). APTgt is an online E-Learning system that supports Communications Disorders (CMDS) faculty during linguistic courses and provides reinforcement activities for phonetic transcription with the potential to improve the quality of students' learning efficacy and teachers' pedagogical experience. In addition, APTgt generates interactive practice sessions and exams, automatic grading, and exam analysis. This paper will focus on the classification module to classify disordered speech and non-disordered speech supporting APTgt. We utilize Mel-frequency cepstral coefficients (MFCCs) and dynamic time warping (DTW) to preprocess the audio files and calculate the similarity, and the Support Vector Machine (SVM) algorithm for classification and regression.

Original languageEnglish (US)
Title of host publicationProceedings - 2021 IEEE 7th International Conference on Collaboration and Internet Computing, CIC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages35-40
Number of pages6
ISBN (Electronic)9781665416252
DOIs
StatePublished - 2021
Event7th IEEE International Conference on Collaboration and Internet Computing, CIC 2021 - Virtual, Online, United States
Duration: Dec 13 2021Dec 15 2021

Publication series

NameProceedings - 2021 IEEE 7th International Conference on Collaboration and Internet Computing, CIC 2021

Conference

Conference7th IEEE International Conference on Collaboration and Internet Computing, CIC 2021
Country/TerritoryUnited States
CityVirtual, Online
Period12/13/2112/15/21

Keywords

  • Dynamic Time Warping
  • E-Learning
  • International Phonetic Alphabet
  • MFCC
  • Phonetic Transcription
  • Speech Classification
  • Support Vector Machine

ASJC Scopus subject areas

  • Hardware and Architecture
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality
  • Computer Networks and Communications

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