Skip to main content
Log in

Speech bandwidth extension using transform-domain data hiding

  • Published:
International Journal of Speech Technology Aims and scope Submit manuscript

Abstract

A new transform-domain speech bandwidth extension algorithm is proposed to transmit the information about the missing speech frequencies over a hidden channel, i.e., the related spectral envelope and gain parameters are hidden within the narrowband speech signal using fast Fourier transform-based data hiding technique. The hidden information is recovered reliably at the receiving end to produce a wideband signal of much higher quality. Obtained results confirm that the excellent reconstructed wideband (RWB) signal quality of the proposed algorithm over the traditional methods.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  • Abel, J., & Fingscheidt, T. (2018). Artificial Speech Bandwidth Extension Using Deep Neural Networks for Wideband Spectral Envelope Estimation. IEEE Transactions on Audio, Speech, and Language Processing, 26(1), 71–83.

    Article  Google Scholar 

  • Bhatt, N., & Kosta, Y. (2015). A novel approach for artificial bandwidth extension of speech signals by LPC technique over proposed GSM FR NB coder using high band feature extraction and various extension of excitation methods. International Journal of Speech Technology, 18(1), 57–64.

    Article  Google Scholar 

  • Can Yag˘lı, M. A., Tug˘tekin, T., & Engin, E. (2013). Artificial bandwidth extension of spectral envelope along a Viterbi path. Speech communication, 55, 111–118.

    Article  Google Scholar 

  • Chen, S., & Leung, H. (2005a). Artificial bandwidth extension of telephony speech by data hiding. In Proceedings of IEEE International Symposium on Circuits and Systems (ISCAS 2005), Kobe, Japan, pp. 3151–3154.

  • Chen, S., & Leung, H. (2005b). Concurrent data transmission through analog speech channel using data hiding. IEEE Signal Processing Letters, 12(8), 581–584.

    Article  Google Scholar 

  • Chen, S., & Leung, H. (2007). Speech bandwidth extension by data hiding and phonetic classification. In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Honolulu, HI, pp. 593–596.

  • Chen, S., Leung, H., & Ding, H. (2007). Telephony speech enhancement by data hiding. IEEE Transactions on instrumentation and measurement, 56(1), 63–74.

    Article  Google Scholar 

  • Chen, Z., Zhao, C., Geng, G., & Yin, F. (2013). An audio watermark based speech bandwidth extension method. EURASIP J. audio, speech and music processing. 2013(10), 1–8.

    Google Scholar 

  • ETSI ES 201 108 V1.1.2 (2000). Speech Processing, Transmission and Quality aspects (STQ); Distributed speech recognition; Front-end feature extraction algorithm; Compression algorithms.

  • Garofolo, J. S. (1993). Getting started with the DARPA TIMIT CD-ROM: An acoustic phonetic continuous speech database. Gaithersburg: National Institute of Standards and Technology (NIST).

    Book  Google Scholar 

  • Geiser, B., & Vary, P. (2007). Backwards Compatible Wideband Telephony in Mobile Networks: CELP Watermarking and Bandwidth Extension. In Proceedings of IEEE International Conference on Acoustics, Speech, and Processing, S. (ICASSP), Honolulu, HI, USA, pp. 533–536.

  • Geiser, B., & Vary, P. (2013). Speech bandwidth extension based on in-band transmission of higher frequencies. In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vancouver, Canada, pp. 7507–7511.

  • Goldsmith, A. (2005). Wireless communications. New York: Cambridge University Press.

    Book  Google Scholar 

  • Hanzo, L. L., Somerville, F. C. A., & Woodard, J. P. (2001). Voice compression and communications: Principles and Applications for fixed and wireless channels. New York: Wiley.

    Book  Google Scholar 

  • Hassan, A. A., Hershey, J. E., & Saulnier, G. J. (1998). Perspectives in spread spectrum. Boston (London): Kluwer Academic Publishers.

    Book  Google Scholar 

  • ITU-T (2001). ITU-T Rec. P.862: Perceptual evaluation of speech quality (PESQ): An objective method for end to-end speech quality assessment of narrow-band telephone networks and speech codecs.

  • Jax, P. (2002). Enhancement of bandlimited speech signals: Algorithms and theoretical bounds. Ph.D. dissertation, Aachen, Germany: RWTH Aachen University.

  • Jax, P., & Vary, P. (2002). An upper bound on the quality of artificial bandwidth extension of narrowband speech signals. In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Orlando, FL, USA, pp. 237–240.

  • Jax, P., & Vary, P. (2003). On artificial bandwidth extension of telephone speech. Signal Processing., 83(8), 1707–1719.

    Article  MATH  Google Scholar 

  • Jax, P., & Vary, P. (2006). Bandwidth extension of speech signals: A catalyst for the introduction of wideband speech coding? IEEE Communication Magazine, 44(5), 106–111.

    Article  Google Scholar 

  • Johannes, A., & Tim, F. (2018). Artificial speech bandwidth extension using deep neural networks for wideband spectral envelope estimation. IEEE/ACM Trans. Audio, Speech, and Lang. Process., 26(1), 71–83.

    Article  Google Scholar 

  • Keiser, B. E., & Strange, E. (1995). Digital telephony and network integration. New York: Van Nostrand Reinhold.

    Book  Google Scholar 

  • Kosta, Y. (2016). Simulation and overall comparative evaluation of performance between different techniques for high band feature extraction based on artificial bandwidth extension of speech over proposed global system for mobile full rate narrow band coder. International Journal of Speech Technology, 19(4), 881–893.

    Article  Google Scholar 

  • Li, Y., & Kang, S. (2016). Artificial bandwidth extension using deep neural network-based spectral envelope estimation and enhanced excitation estimation. IET Signal Processing, 10(4), 422–427.

    Article  Google Scholar 

  • Mukherjee, H., Obaidullah, S. Md, Santosh, K. C., Phadikar, S., & Roy, K. (2018). Line spectral frequency-based features and extreme learning machine for voice activity detection from audio signal. International Journal of Speech Technology, 21(4), 753–760.

    Article  Google Scholar 

  • Nakatoh, Y., Tsushima, M., & Norimatsu, T. (1997). Generation of broadband speech from narrowband speech using piecewise linear mapping. In Proceedings of EUROSPEECH, Rhodes, Greece, pp. 1643–1646.

  • Nilsson, M., & Kleijn, W. B. (2001). Avoiding overestimation in bandwidth extension of telephony speech. In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Salt Lake City, UT, vol. 2, pp. 869–872.

  • Prasad, N., & Kishore Kumar, T. (2016). Bandwidth extension of speech signals: A comprehensive review. International Journal of Intelligent Systems and Applications, 8(2), 45–52.

    Article  Google Scholar 

  • Prasad, N., & Kishore Kumar, T. (2017). Speech bandwidth extension aided by spectral magnitude data hiding. Circuits, Systems, and Signal Processing, 36(11), 4512–4540.

    Article  MATH  Google Scholar 

  • Pulakka, H., & Alku, P. (2011). Bandwidth extension of telephone speech using a neural network and a filter bank implementation for highband Mel spectrum. IEEE Transactions on Acoustics, Speech, and Signal Processing, 19(7), 2170–2183.

    Google Scholar 

  • Rabie, T., & Guerchi, D. (2015). Spectral magnitude speech steganography. International Journal of Computer Applications, 116(5), 1–6.

    Article  Google Scholar 

  • Sagi, A., & Malah, D. (2007). Bandwidth extension of telephone speech aided by data embedding. EURASIP Journal on Advances in Signal Processing. 2007(1., 37–52.

  • Wang, Y., Zhao, S., Qu, D., & Kuang, J. (2016). Speech bandwidth extension using recurrent temporal restricted boltzmann machines. IET Signal Processing Letters, 23(12), 1877–1881.

    Article  Google Scholar 

  • Zhen-Hua, L., Yang, A., Yu, G., & Li-Rong, D. (2018). Waveform modeling and generation using hierarchical recurrent neural networks for speech bandwidth extension. IEEE/ACM Trans. Audio, Speech, and Lang Process, 26(5), 883–894.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Phaneendra Kurada.

Additional information

Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kurada, P., Maruvada, S. & Sanagapallea, K.R. Speech bandwidth extension using transform-domain data hiding. Int J Speech Technol 22, 305–312 (2019). https://doi.org/10.1007/s10772-019-09596-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10772-019-09596-8

Keywords

Navigation