Frame Erasure Concealment in Wideband Speech Coding Based on Large Hidden Markov Model
Shi-Kui Wang, Yibin Tang, You Hongyan, Zhenyang Wu · Journal of Southeast University · 2009
Frame erasure concealment is studied to solve the problem of rapid speech quality reduction due to the loss of speech parameters during speech transmission. A large hidden Markov model is applied to model the immittance spectral frequency (ISF) parameters in AMR-WB codec to optimally estimate the lost ISFs based on the minimum mean square error (MMSE) rule. The estimated ISFs are weighted with the ones of their previous neighbors to smooth the speech, resulting in the actual concealed 1SF vectors. They are used instead of the lost ISFs in the speech synthesis on the receiver. Comparison is made between the speech concealed by this algorithm and by Annex I of G.722.2 specification, and simulation shows that the proposed concealment algorithm can lead to better performance in terms of frequency-weighted spectral distortion and signal-to-noise ratio compared to the baseline method, with an increase of 2.41 dB in signal-to-noise ratio (SNR) and a reduction of 0.885 dB in frequency-weighted spectral distortion.