Title :
A blind bandwidth extension method of audio signals based on Volterra series
Author :
Xingtao Zhang ; Changchun Bao ; Xin Liu ; Liyan Zhang
Author_Institution :
Speech & Audio Signal Process. Lab., Beijing Univ. of Technol., Beijing, China
Abstract :
In this paper, a blind bandwidth extension method of audio signals is proposed in which the fine structure of high-frequency information is recovered based on Volterra series. Combining with Gaussian mixture model and codebook mapping to adjust the spectrum envelope and energy gain of the extended high-frequency components separately, the bandwidth of audio signals is extended to super-wideband from wideband. Furthermore, the proposed method is applied into a real audio codec. The performance of the proposed method is evaluated through objective and subjective tests on the audio signals selected from MPEG items, and it is found that the proposed method outperforms the chaotic prediction method and nearest-neighbor matching method. When the proposed algorithm is applied into ITU-T G.722.1 wideband audio codec, the performance is comparable with that of G.722.1C super-wideband audio codec at 24 kbps.
Keywords :
Gaussian processes; Volterra series; audio coding; codecs; G.722.1C super-wideband audio codec; Gaussian mixture model; ITU-T G.722.1 wideband audio codec; MPEG; Volterra series; audio signals; bit rate 24 kbit/s; blind bandwidth extension method; chaotic prediction method; codebook mapping; energy gain; extended high-frequency components; high-frequency information; nearest-neighbor matching method; spectrum envelope; Codecs; Estimation; Hafnium; Prediction methods; Vectors; Wideband;
Conference_Titel :
Signal & Information Processing Association Annual Summit and Conference (APSIPA ASC), 2012 Asia-Pacific
Conference_Location :
Hollywood, CA
Print_ISBN :
978-1-4673-4863-8