A Robust Narrowband to Wideband Extension System Featuring Enhanced Codebook Mapping

Unno, T.; McCree, Alan

doi:10.1109/icassp.2005.1415236

Cited by 31 publications

(18 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Many efforts have been devoted to artificially generate WB speech from the NB speech. Conventional extension approaches [1,2,3] exploit the mutual dependence between NB and highband (HB) to estimate the missing HB signal from the NB signal. The estimated HB components are then used along with the NB speech to reconstruct a wideband (WB) speech.…”

Section: Introductionmentioning

confidence: 99%

Speech Bandwidth Extension by Data Hiding and Phonetic Classification

Leung

2007

2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07

View full text Add to dashboard Cite

Speech bandwidth extension can be defined as the deliberate process of expanding the frequency range (bandwidth) for speech transmission. Its significant advancement in recent years has led to the technology being adopted commercially in several areas including psychoacoustic bass enhancement of small loudspeakers and the high frequency enhancement of perceptually coded audio. In this paper, a data hiding method based on dither quantization is used for speech bandwidth extension. More specifically, the out-of-band information is encoded and embedded into the narrowband speech without degrading the quality of the bandlimited signal. At the receiver, when the out-of-band information is extracted from the hidden channel, it can be used to combine with the bandlimited signal, providing a signal with a wider bandwidth. To encode the out-of-band speech more efficiently, acoustic phonetic classification is employed to generate three linear prediction (LP) codebook. The simulation results show that compared with using non-classified codebook, the propose scheme have a better bandwidth extension performance in terms of log spectral distortion (LSD).

show abstract

Section: Introductionmentioning

confidence: 99%

Speech Bandwidth Extension by Data Hiding and Phonetic Classification

Leung

2007

2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07

View full text Add to dashboard Cite

show abstract

“…Here our attention focuses on the estimation efficiency of the intended approach rather than the appropriateness of the selected parameters. Hence no other parameters are included in the input vector, despite that the inclusion of additional acoustic features was known to be beneficial to the parameter estimation [3], [4]. In [3], a HMM was utilized to estimate the highband parameters.…”

Section: Hmm-based Approachmentioning

confidence: 99%

“…However, such an idea appears impractical due to the amount of legacy networks already installed. Fortunately, the missing bandwidth can still be partially recovered from narrowband speech via signal processing techniques [1]- [4].…”

Section: Introductionmentioning

confidence: 99%

Combining HMM and Weighted Deviation Linear Transformation for Highband Speech Parameter Estimation

2009

IEICE Trans. Inf. & Syst.

View full text Add to dashboard Cite

SUMMARYA hidden Markov model (HMM)-based parameter estimation scheme is proposed for wideband speech recovery. In each Markov state, the estimation efficiency is improved using a new mapping function derived from the weighted least squares of vector deviations. The experimental results reveal that the performance of the proposed scheme is superior to that combining the HMM and Gaussian mixture model (GMM). key words:wideband recovery, HMM-based parameter estimation, weighted deviation linear transformation

show abstract

“…However, it is difficult to change the current speech transmission infrastructure to provide a wider bandwidth due to economic considerations. An alternate method is to artificially, instead of virtually, extend the speech bandwidth [2,3]. More specifically, the missing high band (HB) components are estimated from the NB speech by exploiting their mutual dependencies.…”

Section: Introductionmentioning

confidence: 99%

Data Hiding for Speech Bandwidth Extension and its Hardware Implementation

Leung

2006

2006 IEEE International Conference on Multimedia and Expo

View full text Add to dashboard Cite

Most of the current speech transmission systems are only able to deliver speech signals in a narrow frequency band. This narrowband speech is characterized by a thin and muffled sound. In this paper, we propose a data hiding scheme to artificially extend the speech bandwidth so that the speech quality can be improved. The hardware perspectives of implementing the proposed scheme are also discussed. A Xilinx MicroBlaze soft processor is used in this study. To balance the trade off between logic resource consumption and processing speed, the data hiding scheme are mainly implemented in application software while fast Fourier transform (FFT) is designed into a hardware acceleration model. Experimental results demonstrate the effectiveness of the proposed data hiding scheme.

show abstract

A Robust Narrowband to Wideband Extension System Featuring Enhanced Codebook Mapping

Cited by 31 publications

References 9 publications

Speech Bandwidth Extension by Data Hiding and Phonetic Classification

Speech Bandwidth Extension by Data Hiding and Phonetic Classification

Combining HMM and Weighted Deviation Linear Transformation for Highband Speech Parameter Estimation

Data Hiding for Speech Bandwidth Extension and its Hardware Implementation

Contact Info

Product

Resources

About