Source and filter estimation for Throat-Microphone speech enhancement
Turan, M. A. T.
IEEE/ACM Transactions on Audio Speech and Language Processing
Institute of Electrical and Electronics Engineers Inc.
265 - 275
Item Usage Stats
MetadataShow full item record
In this paper, we propose a new statistical enhancement system for throat microphone recordings through source and filter separation. Throat microphones (TM) are skin-attached piezoelectric sensors that can capture speech sound signals in the form of tissue vibrations. Due to their limited bandwidth, TM recorded speech suffers from intelligibility and naturalness. In this paper, we investigate learning phone-dependent Gaussian mixture model (GMM)-based statistical mappings using parallel recordings of acoustic microphone (AM) and TM for enhancement of the spectral envelope and excitation signals of the TM speech. The proposed mappings address the phone-dependent variability of tissue conduction with TM recordings. While the spectral envelope mapping estimates the line spectral frequency (LSF) representation of AM from TM recordings, the excitation mapping is constructed based on the spectral energy difference (SED) of AM and TM excitation signals. The excitation enhancement is modeled as an estimation of the SED features from the TM signal. The proposed enhancement system is evaluated using both objective and subjective tests. Objective evaluations are performed with the log-spectral distortion (LSD), the wideband perceptual evaluation of speech quality (PESQ) and mean-squared error (MSE) metrics. Subjective evaluations are performed with an A/B comparison test. Experimental results indicate that the proposed phone-dependent mappings exhibit enhancements over phone-independent mappings. Furthermore enhancement of the TM excitation through statistical mappings of the SED features introduces significant objective and subjective performance improvements to the enhancement of TM recordings. ©2015 IEEE.
KeywordsGaussian mixture model
Mean square error
Gaussian Mixture Model
Line spectral frequencies
Log spectral distortions
Perceptual evaluation of speech qualities
Published Version (Please cite this version)http://dx.doi.org/10.1109/TASLP.2015.2499040
Showing items related by title, author, creator and subject.
Shriberg, E.; Stolcke, A.; Hakkani-Tür, D.; Tür, G. (Elsevier, 2000)A crucial step in processing speech audio data for information extraction, topic detection, or browsing/playback is to segment the input into sentence and topic units. Speech segmentation is challenging, since the cues ...
Çetin, A. Enis; Yardımcı, Y.; Erzin, Engin (IEEE, 1995-05)In this paper, a new set of speech feature representations for robust speech recognition in the presence of car noise are proposed. These parameters are based on subband analysis of the speech signal. Line Spectral Frequency ...
The effects of speech in interference in enclosed leisure spaces : a case of study in Bilkent Roll House, Ankara Gezginer, Pelin Meriç (Bilkent University, 2011)The aim of this study is to investigate the speech interference of users in an open-planned multi-activities public leisure space. Bilkent Roll House was chosen as a leisure space because of its variety of activities in ...