Scheduled System Maintenance:
Some services will be unavailable Sunday, March 29th through Monday, March 30th. We apologize for the inconvenience.
By Topic

Estimation of missing LSF parameters using Gaussian mixture models

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

The purchase and pricing options are temporarily unavailable. Please try again later.
3 Author(s)
Martin, R. ; Inst. of Commun. Syst. & Data Process., Aachen Univ. of Technol., Germany ; Hoelper, C. ; Wittke, I.

Speech transmission over packet networks has to cope with packet delays and packet losses. When a packet loss occurs the missing information must be estimated. We focus on restoring the spectral parameters of a speech coder. A novel approach to estimating missing line spectral frequency (LSF) parameters using Gaussian mixture models (GMM) is proposed. We present the estimation algorithm and study its performance when one or several LSF parameters are lost. We show that a GMM of a relatively low order is sufficient to achieve a substantial improvement in the parameter SNR. Therefore, the new estimation procedure requires much less memory than histogram based estimation methods

Published in:

Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on  (Volume:2 )

Date of Conference:

2001