Mapping Speech Spectra from Throat Microphone to Close-Speaking Microphone: A Neural Network Approach. (16th July 2007)

• Record Type: Journal Article
• Authors: Shahina Shahina, A. A.; Yegnanarayana Yegnanarayana, B. B.
• Other Names: Jan Jan Jiri Jiri Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2007(2007)
• Publication Date: 2007-07-16
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2007/87219
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : Speech recorded from a throat microphone is robust to the surrounding noise, but sounds unnatural unlike the speech recorded from a close-speaking microphone. This paper addresses the issue of improving the perceptual quality of the throat microphone speech by mapping the speech spectra from the throat microphone to the close-speaking microphone. A neural network model is used to capture the speaker-dependent functional relationship between the feature vectors (cepstral coefficients) of the two speech signals. A method is proposed to ensure the stability of the all-pole synthesis filter. Objective evaluations indicate the effectiveness of the proposed mapping scheme. The advantage of this method is that the model gives a smooth estimate of the spectra of the close-speaking microphone speech. No distortions are perceived in the reconstructed speech. This mapping technique is also used for bandwidth extension of telephone speech.