Skip to main content

2016 | OriginalPaper | Buchkapitel

Text-Dependent Versus Text-Independent Speech Emotion Recognition

verfasst von : Biswajit Nayak, Manoj Kumar Pradhan

Erschienen in: Proceedings of the Second International Conference on Computer and Communication Technologies

Verlag: Springer India

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

search-config
loading …

Abstract

The communication between individual and equipment is through speech emotion recognition which plays a vital role and is very exigent to handle. Today, this filed has become an important area of research. It has wide range of applications. This paper analyzes the performance of emotion recognition for eight speakers. Indian Institute of Technology Kharagpur Simulated Hindi Emotional Speech Corpus (IITKGP-SEHSC) emotional speech corpora used for emotions recognition. The sentiments under surveillance for this study are anger, fear, happy, neutral, sarcastic, and surprise. The categorization is prepared using Gaussian mixture model (GMM). Mel-frequency cepstral coefficients (MFCCs) attributes have been used for defining the emotions. We have extracted the percentage of accuracy of emotion for both text-dependent data and text-independent data. We also observed that emotion recognition performance depends on text and speaker. We found that the percentage of accuracy of text-dependent data is more than the text-independent data.

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 Koolagudi, S., Rao, K.S.: Emotion recognition from speech using source, system, and prosodic features. Int. J. Speech Technol. 15, 265–289 (2012)CrossRef Koolagudi, S., Rao, K.S.: Emotion recognition from speech using source, system, and prosodic features. Int. J. Speech Technol. 15, 265–289 (2012)CrossRef
2.
Zurück zum Zitat Ververidis, D., Kotropoulos, C.: Emotional speech recognition: resources, features, and methods. SPC 48, 1162–1181 (2006) Ververidis, D., Kotropoulos, C.: Emotional speech recognition: resources, features, and methods. SPC 48, 1162–1181 (2006)
3.
Zurück zum Zitat Rabiner, L.R., Juang, B.H.: Fundamentals of Speech Recognition. Prentice-Hall, Englewood Cliffs (1993) Rabiner, L.R., Juang, B.H.: Fundamentals of Speech Recognition. Prentice-Hall, Englewood Cliffs (1993)
4.
Zurück zum Zitat Koolagudi, S.G., Maity, S., Kumar, V.A., Chakrabarti, S., Rao, K.S.: IITKGP-SESC: Speech Database for Emotion Analysis, vol. 40, pp. 485–492. Springer, Berlin (2009) Koolagudi, S.G., Maity, S., Kumar, V.A., Chakrabarti, S., Rao, K.S.: IITKGP-SESC: Speech Database for Emotion Analysis, vol. 40, pp. 485–492. Springer, Berlin (2009)
5.
Zurück zum Zitat Koolagudi, S., Reddy, R., Yadav, J., Rao, K.S.: IITKGP-SEHSC: Hindi speech corpus for emotion analysis. In International Conference on Devices and Communications (ICDeCom), pp. 1–5 (2011) Koolagudi, S., Reddy, R., Yadav, J., Rao, K.S.: IITKGP-SEHSC: Hindi speech corpus for emotion analysis. In International Conference on Devices and Communications (ICDeCom), pp. 1–5 (2011)
6.
Zurück zum Zitat Moataz, M.H., Kamel, A.E., Mohamed, S., Fakhreddine, K.: Survey of speech emotion recognition: feature, classification, schemes and databases. Elsevier 44(3), 572–587 (2011) Moataz, M.H., Kamel, A.E., Mohamed, S., Fakhreddine, K.: Survey of speech emotion recognition: feature, classification, schemes and databases. Elsevier 44(3), 572–587 (2011)
7.
Zurück zum Zitat Cheng, X., Duan, Q.: Speech emotion recognition using Gaussian Mixture Model. In: In the 2nd International Conference on Computer Application and System Modeling (2012) Cheng, X., Duan, Q.: Speech emotion recognition using Gaussian Mixture Model. In: In the 2nd International Conference on Computer Application and System Modeling (2012)
8.
Zurück zum Zitat Thapliyal, N., Amoli, G.: Speech based emotion recognition with Gaussian Mixture Model. Int. J. Adv. Res. Comput. Eng. Technol. 1, 65–69 (2012) Thapliyal, N., Amoli, G.: Speech based emotion recognition with Gaussian Mixture Model. Int. J. Adv. Res. Comput. Eng. Technol. 1, 65–69 (2012)
9.
Zurück zum Zitat Reynolds, D.: Gaussian mixture models: MIT Lincoln Laboratory, 244 St Wood, emotion recognition using support vector regression. In: 10th International Society for Music Information Retrieval Conference (ISMIR 2009) Reynolds, D.: Gaussian mixture models: MIT Lincoln Laboratory, 244 St Wood, emotion recognition using support vector regression. In: 10th International Society for Music Information Retrieval Conference (ISMIR 2009)
10.
Zurück zum Zitat Wankhade, S.B., Tijare, P., Chavhan, Y.: Speech emotion recognition system using SVM AND LIBSVM. Int. J. Comput. Sci. Appl. 4(2) (2011) ISSN: 0974-1003 Wankhade, S.B., Tijare, P., Chavhan, Y.: Speech emotion recognition system using SVM AND LIBSVM. Int. J. Comput. Sci. Appl. 4(2) (2011) ISSN: 0974-1003
11.
Zurück zum Zitat Khanna, M.P., Kumar, S., Toscano-Medina, K., Nakano, M., Meana, H.P.: Application of vector quantization in emotion recognition from human speech. Inf. Intell. Syst. Technol. Manage. Commun. Comput. Inf. Sci. 141, 118–125 (2011) Khanna, M.P., Kumar, S., Toscano-Medina, K., Nakano, M., Meana, H.P.: Application of vector quantization in emotion recognition from human speech. Inf. Intell. Syst. Technol. Manage. Commun. Comput. Inf. Sci. 141, 118–125 (2011)
12.
Zurück zum Zitat Panda, B., Padhi, D., Dash, K., Mohanty, S.: Use of SVM classifier & MFCC in speech emotion recognition system. IJARCSSE 2(3) (2012) ISSN: 2277128X Panda, B., Padhi, D., Dash, K., Mohanty, S.: Use of SVM classifier & MFCC in speech emotion recognition system. IJARCSSE 2(3) (2012) ISSN: 2277128X
13.
Zurück zum Zitat Olivares-Mercado, J., Aguilar, G., Toscano-Medina, K., Nakano, M., Meana, H.P.: GMM versus SVM for face recognition and face verification. In: Corcoran, P. (ed.) Reviews, Refinements and New Ideas in Face Recognition (2011). ISBN: 978-953-307-368-2 Olivares-Mercado, J., Aguilar, G., Toscano-Medina, K., Nakano, M., Meana, H.P.: GMM versus SVM for face recognition and face verification. In: Corcoran, P. (ed.) Reviews, Refinements and New Ideas in Face Recognition (2011). ISBN: 978-953-307-368-2
14.
Zurück zum Zitat Utane, A.S., Nalbalwar, S.L.: Emotion recognition through speech using gaussian mixture model and hidden markov model. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 3(4) (2013). ISSN: 2277 128X Utane, A.S., Nalbalwar, S.L.: Emotion recognition through speech using gaussian mixture model and hidden markov model. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 3(4) (2013). ISSN: 2277 128X
Metadaten
Titel
Text-Dependent Versus Text-Independent Speech Emotion Recognition
verfasst von
Biswajit Nayak
Manoj Kumar Pradhan
Copyright-Jahr
2016
Verlag
Springer India
DOI
https://doi.org/10.1007/978-81-322-2517-1_16