Skip to main content
Erschienen in:
Buchtitelbild

2015 | OriginalPaper | Buchkapitel

1. Introduction

verfasst von : K. Sreenivasa Rao, Dipanjan Nandi

Erschienen in: Language Identification Using Excitation Source Features

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

This chapter introduces the basic goal of language identification (LID) and its impacts on real-life applications. A brief overview of the basic features used for developing LID systems has been given and different categories of LID systems are also discussed here. Eventually, the primary issues in developing LID systems and the major contributions of this book towards solving those issues have been highlighted.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat V.M. Vanishree, Provision for Linguistic Diversity and Linguistic Minorities in India. Master’s thesis. Applied Linguistics, St. Mary’s University College, Strawberry Hill, London, February 2011 V.M. Vanishree, Provision for Linguistic Diversity and Linguistic Minorities in India. Master’s thesis. Applied Linguistics, St. Mary’s University College, Strawberry Hill, London, February 2011
2.
Zurück zum Zitat F. Runstein, F. Violaro, An isolated-word speech recognition system using neural networks. Circuits Syst. 1, 550–553 (1995) F. Runstein, F. Violaro, An isolated-word speech recognition system using neural networks. Circuits Syst. 1, 550–553 (1995)
3.
Zurück zum Zitat A. Kocsor, L. Toth, Application of Kernel-based feature space transformations and learning methods to phoneme classification. Appl. Intell. 21, 129–142 (2004)CrossRefMATH A. Kocsor, L. Toth, Application of Kernel-based feature space transformations and learning methods to phoneme classification. Appl. Intell. 21, 129–142 (2004)CrossRefMATH
4.
Zurück zum Zitat R. Halavati, S.B. Shouraki, S.H. Zadeh, Recognition of human speech phonemes using a novel fuzzy approach. Appl. Soft Comput. 7, 828–839 (2007)CrossRef R. Halavati, S.B. Shouraki, S.H. Zadeh, Recognition of human speech phonemes using a novel fuzzy approach. Appl. Soft Comput. 7, 828–839 (2007)CrossRef
5.
Zurück zum Zitat T. Hao, M. Chao-Hong, L. Lin-Shan, An initial attempt for phoneme recognition using Structured Support Vector Machine (SVM), in IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), pp. 4926–4929 (2010) T. Hao, M. Chao-Hong, L. Lin-Shan, An initial attempt for phoneme recognition using Structured Support Vector Machine (SVM), in IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), pp. 4926–4929 (2010)
6.
Zurück zum Zitat S. Furui, Cepstral analysis techniques for automatic speaker verification. IEEE Trans. Audio Speech Lang. Process. 29(2), 254–272 (1981)CrossRef S. Furui, Cepstral analysis techniques for automatic speaker verification. IEEE Trans. Audio Speech Lang. Process. 29(2), 254–272 (1981)CrossRef
7.
Zurück zum Zitat D.A. Reynolds, R.C. Rose, Robust text-independent speaker identification using Gaussian mixture speaker models. IEEE Trans. Audio, Speech Lang. Process. 3(1), 4–17 (1995) D.A. Reynolds, R.C. Rose, Robust text-independent speaker identification using Gaussian mixture speaker models. IEEE Trans. Audio, Speech Lang. Process. 3(1), 4–17 (1995)
8.
Zurück zum Zitat D.A. Reynolds, Speaker identification and verification using gaussian mixture speaker models. Speech Commun. 17, 91–108 (1995)CrossRef D.A. Reynolds, Speaker identification and verification using gaussian mixture speaker models. Speech Commun. 17, 91–108 (1995)CrossRef
9.
Zurück zum Zitat M. Sugiyama, Automatic language recognition using acoustic features, in IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 813–816, May 1991 M. Sugiyama, Automatic language recognition using acoustic features, in IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 813–816, May 1991
10.
Zurück zum Zitat K.S. Rao, S. Maity, V.R. Reddy, Pitch synchronous and glottal closure based speech analysis for language recognition. Int. J. Speech Technol. (Springer) 16(4), 413–430 (2013)CrossRef K.S. Rao, S. Maity, V.R. Reddy, Pitch synchronous and glottal closure based speech analysis for language recognition. Int. J. Speech Technol. (Springer) 16(4), 413–430 (2013)CrossRef
11.
Zurück zum Zitat J. Balleda, H.A. Murthy, T. Nagarajan, Language identification from short segments of speech. in International Conference on Spoken Language Processing (ICSLP), pp. 1033–1036, October 2000 J. Balleda, H.A. Murthy, T. Nagarajan, Language identification from short segments of speech. in International Conference on Spoken Language Processing (ICSLP), pp. 1033–1036, October 2000
12.
Zurück zum Zitat V.R. Reddy, S. Maity, K.S. Rao, Recognition of Indian languages using multi-level spectral and prosodic features. Int. J. Speech Technol. (Springer) 16(4), 489–510 (2013)CrossRef V.R. Reddy, S. Maity, K.S. Rao, Recognition of Indian languages using multi-level spectral and prosodic features. Int. J. Speech Technol. (Springer) 16(4), 489–510 (2013)CrossRef
13.
Zurück zum Zitat S.G. Koolagudi, K. Sreenivasa Rao, Emotion recognition from speech using sub-syllabic and pitch synchronous spectral features. Int. J. Speech Technol. (Springer) 15(3), 495–511 (2012)CrossRef S.G. Koolagudi, K. Sreenivasa Rao, Emotion recognition from speech using sub-syllabic and pitch synchronous spectral features. Int. J. Speech Technol. (Springer) 15(3), 495–511 (2012)CrossRef
14.
Zurück zum Zitat K. Sreenivasa Rao, S.G. Koolagudi, Emotion Recognition using Speech Features. (Springer, 2012). ISBN 978-1-4614-5142-6 K. Sreenivasa Rao, S.G. Koolagudi, Emotion Recognition using Speech Features. (Springer, 2012). ISBN 978-1-4614-5142-6
15.
Zurück zum Zitat K. Sreenivasa Rao, S.G. Koolagudi, Robust Emotion Recognition Using Spectral And Prosodic Features. (Springer, 2012). ISBN 978-1-4614-6359-7 K. Sreenivasa Rao, S.G. Koolagudi, Robust Emotion Recognition Using Spectral And Prosodic Features. (Springer, 2012). ISBN 978-1-4614-6359-7
16.
Zurück zum Zitat S.G. Koolagudi, D. Rastogi, K. Sreenivasa Rao, Spoken language identification using spectral features. Communications in Computer and Information Science (CCIS): Contemporary Computing, vol. 306, (Springer, 2012), pp. 496–497 S.G. Koolagudi, D. Rastogi, K. Sreenivasa Rao, Spoken language identification using spectral features. Communications in Computer and Information Science (CCIS): Contemporary Computing, vol. 306, (Springer, 2012), pp. 496–497
17.
Zurück zum Zitat D. Neiberg, K. Elenius, K. Laskowski, Emotion recognition in spontaneous speech using GMMs, in Internation Speech Communication and Association (INTERSPEECH), September 2006 D. Neiberg, K. Elenius, K. Laskowski, Emotion recognition in spontaneous speech using GMMs, in Internation Speech Communication and Association (INTERSPEECH), September 2006
18.
Zurück zum Zitat D. Bitouk, R. Verma, A. Nenkova, Class-level spectral features for emotion recognition. Speech Commun. 52(7), 613–625 (2009) D. Bitouk, R. Verma, A. Nenkova, Class-level spectral features for emotion recognition. Speech Commun. 52(7), 613–625 (2009)
19.
Zurück zum Zitat K.S. Rao, B. Yegnanarayana, Modeling durations of syllables using neural networks. Comput. Speech Lang. 21, 282–295 (2007)CrossRef K.S. Rao, B. Yegnanarayana, Modeling durations of syllables using neural networks. Comput. Speech Lang. 21, 282–295 (2007)CrossRef
20.
Zurück zum Zitat A.G. Adami, R. Mihaescu, D.A. Reynolds, J.J. Godfrey, Modeling prosodic dynamics for speaker recognition, in IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), vol. 4, April 2003 A.G. Adami, R. Mihaescu, D.A. Reynolds, J.J. Godfrey, Modeling prosodic dynamics for speaker recognition, in IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), vol. 4, April 2003
21.
Zurück zum Zitat L. Mary, B. Yegnanarayana, Extraction and representation of prosodic features for language and speaker recognition. Speech Commun. 50(10), 782–796 (2008)CrossRef L. Mary, B. Yegnanarayana, Extraction and representation of prosodic features for language and speaker recognition. Speech Commun. 50(10), 782–796 (2008)CrossRef
22.
Zurück zum Zitat K.S. Rao, S.G. Koolagudi, R.R. Vempada, Emotion recognition from speech using global and local prosodic features. Int. J. Speech Technol. 16(2), 143–160 (2013)CrossRef K.S. Rao, S.G. Koolagudi, R.R. Vempada, Emotion recognition from speech using global and local prosodic features. Int. J. Speech Technol. 16(2), 143–160 (2013)CrossRef
23.
Zurück zum Zitat K. Sreenivasa Rao, S.G. Koolagudi, Identification of hindi dialects and emotions using spectral and prosodic features of speech. J. Syst. Cybern. Inform. 9(4), 24–33 (2011) K. Sreenivasa Rao, S.G. Koolagudi, Identification of hindi dialects and emotions using spectral and prosodic features of speech. J. Syst. Cybern. Inform. 9(4), 24–33 (2011)
24.
Zurück zum Zitat J. Yadav, K. Sreenivasa Rao, Emotional-speech synthesis from neutral-speech using prosody imposition, in International Conference on Recent Trends in Computer Science and Engineering (ICRTCSE-2014), Central University of Bihar, Patna, India, 8–9, February 2014 J. Yadav, K. Sreenivasa Rao, Emotional-speech synthesis from neutral-speech using prosody imposition, in International Conference on Recent Trends in Computer Science and Engineering (ICRTCSE-2014), Central University of Bihar, Patna, India, 8–9, February 2014
25.
Zurück zum Zitat D. Martinez, L. Burget, L. Ferrer, N. Scheffer, i-vector based prosodic system for language identification, in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4861–4864, March 2012 D. Martinez, L. Burget, L. Ferrer, N. Scheffer, i-vector based prosodic system for language identification, in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4861–4864, March 2012
26.
Zurück zum Zitat J. Makhoul, Linear prediction: a tutorial review. Proc. IEEE 63(4), 561–580 (1975)CrossRef J. Makhoul, Linear prediction: a tutorial review. Proc. IEEE 63(4), 561–580 (1975)CrossRef
27.
Zurück zum Zitat B. Yegnanarayana, T.K. Raja, Performance of linear prediction analysis on speech with additive noise, in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (1977) B. Yegnanarayana, T.K. Raja, Performance of linear prediction analysis on speech with additive noise, in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (1977)
28.
Zurück zum Zitat C.S. Gupta, S.R.M. Prasanna, B. Yegnanarayana, Autoassociative neural network models for online speaker verification using source features from vowels, in IEEE International Joint Conference Neural Networks May 2002 C.S. Gupta, S.R.M. Prasanna, B. Yegnanarayana, Autoassociative neural network models for online speaker verification using source features from vowels, in IEEE International Joint Conference Neural Networks May 2002
29.
Zurück zum Zitat D. Pati, S.R.M. Prasanna, Subsegmental, segmental and suprasegmental processing of linear prediction residual for speaker information. Int. J. Speech Technol. (Springer) 14(1), 49–63 (2011)CrossRef D. Pati, S.R.M. Prasanna, Subsegmental, segmental and suprasegmental processing of linear prediction residual for speaker information. Int. J. Speech Technol. (Springer) 14(1), 49–63 (2011)CrossRef
30.
Zurück zum Zitat D. Pati, D. Nandi, K. Sreenivasa Rao, Robustness of excitation source information for language independent speaker recognition, in 16th International Oriental COCOSDA Conference, Gurgoan, India, November 2013 D. Pati, D. Nandi, K. Sreenivasa Rao, Robustness of excitation source information for language independent speaker recognition, in 16th International Oriental COCOSDA Conference, Gurgoan, India, November 2013
31.
Zurück zum Zitat D. Pati, S.R.M. Prasanna, A comparative study of explicit and implicit modelling of subsegmental speaker-specific excitation source information. Sadhana (Springer) 38(4), 591–620 (2013) D. Pati, S.R.M. Prasanna, A comparative study of explicit and implicit modelling of subsegmental speaker-specific excitation source information. Sadhana (Springer) 38(4), 591–620 (2013)
32.
Zurück zum Zitat A. Bajpai, B. Yegnanarayana, Exploring features for audio clip classification using LP residual and AANN models, in International Conference on Intelligent Sensing and Information Processing, pp. 305–310, January 2004 A. Bajpai, B. Yegnanarayana, Exploring features for audio clip classification using LP residual and AANN models, in International Conference on Intelligent Sensing and Information Processing, pp. 305–310, January 2004
33.
Zurück zum Zitat K.S. Rao, S.G. Koolagudi, Characterization and recognition of emotions from speech using excitation source information. Int. J. Speech Technol. (Springer) 16, 181–201 (2013)CrossRef K.S. Rao, S.G. Koolagudi, Characterization and recognition of emotions from speech using excitation source information. Int. J. Speech Technol. (Springer) 16, 181–201 (2013)CrossRef
34.
Zurück zum Zitat A.V. Singh, J. Mukhopadhyay, K. Sreenivasa Rao, K. Viswanath, Classification of infant cries using dynamics of epoch features. J. Intell. Syst. 22(3), 253–267 (2013) A.V. Singh, J. Mukhopadhyay, K. Sreenivasa Rao, K. Viswanath, Classification of infant cries using dynamics of epoch features. J. Intell. Syst. 22(3), 253–267 (2013)
35.
Zurück zum Zitat A.V. Singh, J. Mukhopadyay, S.B.S. Kumar, K. Sreenivasa Rao, Infant cry recognition using excitation source features, in IEEE INDICON, Mumbai, India, December 2013 A.V. Singh, J. Mukhopadyay, S.B.S. Kumar, K. Sreenivasa Rao, Infant cry recognition using excitation source features, in IEEE INDICON, Mumbai, India, December 2013
36.
Zurück zum Zitat S.R.M. Prasanna, C.S. Gupta, B. Yegnanarayana, Extraction of speaker-specific excitation information from linear prediction residual of speech. Speech Commun. 48, 1243–1261 (2006)CrossRef S.R.M. Prasanna, C.S. Gupta, B. Yegnanarayana, Extraction of speaker-specific excitation information from linear prediction residual of speech. Speech Commun. 48, 1243–1261 (2006)CrossRef
Metadaten
Titel
Introduction
verfasst von
K. Sreenivasa Rao
Dipanjan Nandi
Copyright-Jahr
2015
DOI
https://doi.org/10.1007/978-3-319-17725-0_1

Neuer Inhalt