Skip to main content

Recognition of Marathi Numerals Using MFCC and DTW Features

  • Conference paper
  • First Online:
  • 976 Accesses

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1037))

Abstract

Numeral recognition is one amongst the foremost important problems in pattern recognition. Its numerous uses like reading communication postal code, worker code, bank cheque method etc. To the simplest of our information, very less work has been wiped out Marathi language as compared with other Indian and non-Indian languages. It has mentioned a unique technique for recognition of isolated Marathi numerals. It introduces Marathi numerals and identification technique using MFCC and DTW as attributes. The accuracy of the pre-recorded samples is greater than that of online testing samples. We have got additionally seen that the accuracy of the speaker dependent samples is over that of the speaker independent samples. Another technique known as HMM is additionally discussed. By experimentation, it’s ascertained that identification exactness is higher for HMM than DTW, but the training method in DTW is extremely straightforward and quick, as compared to HMM. The time needed for recognition of numerals using HMM is additional as compared to DTW, because it should bear the various states, iterations and lots of additional mathematical modeling, thus DTW is most well-liked for the real-time applications.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Saon, G., Picheny, M.: Recent advances in conversational speech recognition using convolutional and recurrent neural networks. IBM J. Res. Dev. 61(4/5), 1 (2017)

    Article  Google Scholar 

  2. O’Shaughnessy, D.: Automatic speech recognition. In: CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON) (2015). https://doi.org/10.1109/chilecon.2015.7400411

  3. Rabiner, L.R., Schafer, R.W.: Digital Processing Of Speech Signals, Low Price Edition. Pearson, London (2007)

    Google Scholar 

  4. Anusuya, M.A., Katti, S.K.: Speech recognition by machine: a review. (IJCSIS) Int. J. Comput. Sci. Inf. Secur. 6(3), 181–205 (2009)

    Google Scholar 

  5. Gawali, B.W., Gaikwad, S., Yannawar, P., Mehrotra, S.C.: Marathi isolated word recognition system using MFCC and DTW features. In: Proceedings of International Conference of Advances in Computer Science (2010)

    Google Scholar 

  6. Muda, L., Begam, M., Elamvazuth, I.: Voice recognition algorithms using Mel Frequency Cepstral Coefficient (MFCC) and Dynamic Time Warping (DTW) techniques. J. Comput. 2(3) (2010). ISSN 2151-9617

    Google Scholar 

  7. Vimala, C., Radhab, V.: Speaker independent isolated speech recognition system for Tamil language using HMM. In: International Conference on Communication Technology and System Design (2011)

    Google Scholar 

  8. Bala, A., Kumar, A., Birla, N.: Voice command recognition system based on MFCC and DTW. Int. J. Eng. Sci. Technol. 2(12), 7335–7342 (2010)

    Google Scholar 

  9. Jiang, H., Li, X., Liu, C.: Large margin hidden Markov models for speech recognition. IEEE Trans. Audio Speech Lang. Process. 14(5) (2006)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Siddheshwar S. Gangonda .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Gangonda, S.S., Patavardhan, P.P., Karande, K.J. (2019). Recognition of Marathi Numerals Using MFCC and DTW Features. In: Santosh, K., Hegadi, R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1037. Springer, Singapore. https://doi.org/10.1007/978-981-13-9187-3_17

Download citation

  • DOI: https://doi.org/10.1007/978-981-13-9187-3_17

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9186-6

  • Online ISBN: 978-981-13-9187-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics