2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information
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Paper Detail

Paper IDAUD-14.2
Paper Title DETECTING SIGNAL CORRUPTIONS IN VOICE RECORDINGS FOR SPEECH THERAPY
Authors Helmer Nylén, Saikat Chatterjee, Sten Ternström, KTH Royal Institute of Technology, Sweden
SessionAUD-14: Quality and Intelligibility Measures
LocationGather.Town
Session Time:Wednesday, 09 June, 15:30 - 16:15
Presentation Time:Wednesday, 09 June, 15:30 - 16:15
Presentation Poster
Topic Audio and Acoustic Signal Processing: [AUD-MAAE] Modeling, Analysis and Synthesis of Acoustic Environments
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract In this article we design an experimental setup to detect disturbances in voice recordings, such as additive noise, clipping, infrasound and random muting. The datasets are generated by introducing degradations into clean recordings. We test five different classification algorithms in both single- and multi-label settings: kernel substitution based support vector machine, convolutional neural network, long short-term memory (LSTM), and a hidden Markov model using either Gaussian mixture models or generative models in its state distribution. The LSTM achieved good results in both tests, most notably in the multi-label case where the average balanced accuracy was 82.7% on one dataset.