Spoken digit recognition in portuguese using line spectral frequencies

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7637 LNAI, Issue , 2012, Pages 241-250

  Silva, Diego F ^a   De Souza, Vinícius M A ^a   Batista, Gustavo E A P A ^a   Giusti, Rafael ^a  

^a UNIVERSITY OF SÃO PAULO   (Brazil)

Author keywords

Line spectral frequency; Machine learning; Speech recognition; Spoken digit recognition

Indexed keywords

ARTIFICIAL INTELLIGENCE; LEARNING ALGORITHMS; LEARNING SYSTEMS; SIGNAL ENCODING;

ATTRIBUTE EXTRACTION; BANK TRANSACTIONS; COMBINATION OF CLASSIFIERS; DIGIT RECOGNITION; LINE SPECTRAL FREQUENCIES; MEL FREQUENCY CEPSTRUM COEFFICIENTS; SHORT PERIODS; STATE-OF-THE-ART METHODS;

SPEECH RECOGNITION;

EID: 84906686752     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-34654-5_25     Document Type: Conference Paper

References (18)

1. Abushariah, A., Gunawan, T., Khalifa, O., Abushariah, M.: English Digits Speech Recognition System Based on Hidden Markov Models. In: Intl. Conf. on Computer and Communication Engineering (ICCCE 2010), pp. 1-5. IEEE (2010)
2. Alotaibi, Y.: Investigating Spoken Arabic Digits in Sspeech Recognition Setting. Information Sciences 173(1), 115-139 (2005)
3. Azam, S., Mansoor, Z., Mughal, M., Mohsin, S.: Urdu Spoken Digits Recognition Using Classified MFCC and Backpropgation Neural Network. In: Computer Graphics, Imaging and Visualisation (CGIV 2007), pp. 414-418. IEEE (2007)
4. Bresolin, A.A., Neto, A.D.D., Alsina, P.J.: Digit Recognition Using Wavelet and SVM in Brazilian Portuguese. In: International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008), pp. 1545-1548. IEEE (2008)
5. Ghanty, S., Shaikh, S., Chaki, N.: On Recognition of Spoken Bengali Numerals. In: International Conference on Computer Information Systems and Industrial Management Applications (CISIM 2010), pp. 54-59. IEEE (2010)
6. Hu, X., Zhan, L., Xue, Y., Zhou, W., Zhang, L.: Spoken Arabic Digits Recognition Based onWavelet Neural Networks. In: IEEE International Conference on Systems, Man, and Cybernetics (SMC 2011), pp. 1481-1485. IEEE (2011)
7. Itakura, F.: Line Spectrum Represen tation of Linear Predictor Coefficients of Speech Signals. The Journal of the Acoustical Society of America 57, S35 (1975)
8. Kondo, K., Kamata, H., Ishida, Y.: Speaker-Independent Spoken Digits Recognition Using LVQ. In: IEEE World Congress on Computational Intelligence (WCCI 1994), vol. 7, pp. 4448-4451 (1994)
9. Kopparapu, S., Rao, P.: Enhancing Spoken Connected-Digit Recognition Accuracy by Error Correction Codes-A Novel Scheme. Sadhana 29(5), 559-571 (2004)
10. Markel, J., Gray, A.: Linear Prediction of Speech. Springer (1976)
11. Oppenheim, A., Sc hafer, R., Buck, J.: Discrete-Time Signal Processing. Prentice-Hall (1989)
12. Paliwal, K., Kleijn, W.: Quantization of LPC Parameters. In: Speech Coding and Synthesis, pp. 433-466. Elsevier (1995)
13. Panwar, M., Sharma, R., Khan, I., Farooq, O.: Design ofWavelet Based Features for Recognition of Hindi Digits. In: Intl. Conference on Multimedia, Signal Processing and Communication Techno logies (IMPACT 2011), pp. 232-235 (2011)
14. Rabiner, L., Schafer, R.: Digital Processing of Speech Signals. Prentice-Hall (1978)
15. Rodrigues, F., Trancoso, I.: Digit Recognition Using the SPEECHDAT Corpus. In: 2nd Conference on Telecommunications (CONFETELE 1999), pp. 1-4 (1999)
16. Stevens, S.S., Volkmann, J., Newman, E.B.: A Scale for the Measurement of the Psychological Magnitude Pitch. Journal of the Acoustical Society of America 8(3), 185-190 (1937)
17. Watson, A.: Image Compression Using the Discrete Cosine Transform. Mathematica Journal 4(1), 81-88 (1994).
18. Zhen B.,.Wu X.,Liu Z.,Chi H.,On the importance of components of the mfcc in speech and speaker recognition ,6th International Conference on Spoken Language Processing (ICSLP 2000, 487-490, 2000. Nível Superior