Araştırma Makalesi
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Correlogram Based Feature Selectıon For Speaker Identıfıcatıon Usıng Vowels

Yıl 2000, Cilt: 13 Sayı: 2, 14 - 13, 31.12.2000

Öz

A correlogrcnn approach to the seîection of text-dependent feaîures m

vcweî souncis is invesiigaîed for speaker identificaîion. in the approach, vowel sounds

as the idenîity carrying parts in spoken utterances are represented m the form of a

correlogram, m whıch the speaker dependent spectral and temporaî information is

codsd. Psycho-physiologıcally motivated speclro-temporal correlation with a search

algoriihm is introduced to identify the regions vhere the relevanl features are

embedded thal are suited to discrimination. We identify Ihefeature regionsfor a set of

ındividuaî vowel sounds, and present resulîs on their effectiveness in identifying

speakers. Partıculccr to îhe approach is thaî U makes no explicit use of any individîial

speech features.

Kaynakça

  • [l] J. P. Campbell, "Speaker recognition: A tutorial", IEEE Proceedings, 85(9), pp 1437-1462. 1997.
  • [2] M. R. Sambur, "Selection of acoustic features for speaker identification", IEEE Trans. Acoustics, Speech, and Signal Processing, ASSP-23(2), pp 176-182, 1975.
  • [3] C C. Johnson, H. Hollien imd J. W. Hicks, "Speaker identification utilizing selected temporal features", J. Phonetics, 12, pp 19-326, 1984.
  • [4] F. K. Soong and A. E. Rosenberg, "On the use of instantaneous and transitional spectral information in speaker recognition", JEEE Trans. Acoustics, Speech, and Signal Processing, ASSP-36(6), pp 871-879, 1988.
  • [5] M. Slaney and R. F. Lyon, "On the importance oftime - a temporal representatioıı of sound", in Visual Representations of Speech Signals, by Martin Cooke, Steve Beet and Malcolm Crawford (eds.), Wiley, 1993, pp 279-284.
  • [6] J. M. Colombi, T. R. Anderson, S. K. Rogers, D. W. Ruck and G. T. Warhola, Auditory model representation and comparison for speaker recognition", IEEE Proc. Int. Conf On Neural Networks, 1993, pp 1914-1919.
  • [7] T. R. Anderson and R. D. Patterson, "Speaker recognition with the auditory image model and self organizing feature maps: A comparison with traditional techniques", ESCA Workshop on Automatic Speaker Recognitİon, Martigny Apdl 5-7, 1994, pp 153-156.
  • [8] X. Jiang, 2. Gong, F. Sun and H. Chi, "A speaker recognition system based on auditory model, World Congress on Neural Network, Int. Neural Network Society Annual Meeting, SanDiego, 1994, (4), Ch. 128, D595-D600.
  • [9] F. Ertaş, Ses sinyallerine karşı basilar membran hareketinin benzetimi", Elektrik- Elektronik-Bilgisayar Müh. 8. Ulusal Kongresi, Gaziantep, 1999, pp. 618-621,
  • [10] R. Meddis, "Simulation of auditory-neural transduction: Further studies", Journ. of Acous. Sac. ofAmenca, JASA 83(3), pp 1056-1063, 1988.
  • [11] B. C J Moore, An introduction to the psychology of hearmg", Academic Press, 1989.
  • [12] B, S. Atal, Automatic recognition of speakers from their voices", IEEE Proceedings, 64(4), pp 460-475, 1976.
  • [13] K. K. Paliwal, "Effectiveness of different vowel sounds in automatic speaker ıdentification", J. Phonetics, 12, pp 17-21, 1984.

Correlogram Based Feature Selectıon For Speaker Identıfıcatıon Usıng Vowels

Yıl 2000, Cilt: 13 Sayı: 2, 14 - 13, 31.12.2000

Öz

A correlogrcnn approach to the seîection of text-dependent feaîures m
vcweî souncis is invesiigaîed for speaker identificaîion. in the approach, vowel sounds
as the idenîity carrying parts in spoken utterances are represented m the form of a
correlogram, m whıch the speaker dependent spectral and temporaî information is
codsd. Psycho-physiologıcally motivated speclro-temporal correlation with a search
algoriihm is introduced to identify the regions vhere the relevanl features are
embedded thal are suited to discrimination. We identify Ihefeature regionsfor a set of
ındividuaî vowel sounds, and present resulîs on their effectiveness in identifying
speakers. Partıculccr to îhe approach is thaî U makes no explicit use of any individîial
speech features.

Kaynakça

  • [l] J. P. Campbell, "Speaker recognition: A tutorial", IEEE Proceedings, 85(9), pp 1437-1462. 1997.
  • [2] M. R. Sambur, "Selection of acoustic features for speaker identification", IEEE Trans. Acoustics, Speech, and Signal Processing, ASSP-23(2), pp 176-182, 1975.
  • [3] C C. Johnson, H. Hollien imd J. W. Hicks, "Speaker identification utilizing selected temporal features", J. Phonetics, 12, pp 19-326, 1984.
  • [4] F. K. Soong and A. E. Rosenberg, "On the use of instantaneous and transitional spectral information in speaker recognition", JEEE Trans. Acoustics, Speech, and Signal Processing, ASSP-36(6), pp 871-879, 1988.
  • [5] M. Slaney and R. F. Lyon, "On the importance oftime - a temporal representatioıı of sound", in Visual Representations of Speech Signals, by Martin Cooke, Steve Beet and Malcolm Crawford (eds.), Wiley, 1993, pp 279-284.
  • [6] J. M. Colombi, T. R. Anderson, S. K. Rogers, D. W. Ruck and G. T. Warhola, Auditory model representation and comparison for speaker recognition", IEEE Proc. Int. Conf On Neural Networks, 1993, pp 1914-1919.
  • [7] T. R. Anderson and R. D. Patterson, "Speaker recognition with the auditory image model and self organizing feature maps: A comparison with traditional techniques", ESCA Workshop on Automatic Speaker Recognitİon, Martigny Apdl 5-7, 1994, pp 153-156.
  • [8] X. Jiang, 2. Gong, F. Sun and H. Chi, "A speaker recognition system based on auditory model, World Congress on Neural Network, Int. Neural Network Society Annual Meeting, SanDiego, 1994, (4), Ch. 128, D595-D600.
  • [9] F. Ertaş, Ses sinyallerine karşı basilar membran hareketinin benzetimi", Elektrik- Elektronik-Bilgisayar Müh. 8. Ulusal Kongresi, Gaziantep, 1999, pp. 618-621,
  • [10] R. Meddis, "Simulation of auditory-neural transduction: Further studies", Journ. of Acous. Sac. ofAmenca, JASA 83(3), pp 1056-1063, 1988.
  • [11] B. C J Moore, An introduction to the psychology of hearmg", Academic Press, 1989.
  • [12] B, S. Atal, Automatic recognition of speakers from their voices", IEEE Proceedings, 64(4), pp 460-475, 1976.
  • [13] K. K. Paliwal, "Effectiveness of different vowel sounds in automatic speaker ıdentification", J. Phonetics, 12, pp 17-21, 1984.
Toplam 13 adet kaynakça vardır.

Ayrıntılar

Konular Elektrik Mühendisliği
Bölüm Araştırma Makaleleri
Yazarlar

Figen Ertaş

Yayımlanma Tarihi 31 Aralık 2000
Yayımlandığı Sayı Yıl 2000 Cilt: 13 Sayı: 2

Kaynak Göster

APA Ertaş, F. (2000). Correlogram Based Feature Selectıon For Speaker Identıfıcatıon Usıng Vowels. Eskişehir Osmangazi Üniversitesi Mühendislik Ve Mimarlık Fakültesi Dergisi, 13(2), 14-13.
AMA Ertaş F. Correlogram Based Feature Selectıon For Speaker Identıfıcatıon Usıng Vowels. ESOGÜ Müh Mim Fak Derg. Aralık 2000;13(2):14-13.
Chicago Ertaş, Figen. “Correlogram Based Feature Selectıon For Speaker Identıfıcatıon Usıng Vowels”. Eskişehir Osmangazi Üniversitesi Mühendislik Ve Mimarlık Fakültesi Dergisi 13, sy. 2 (Aralık 2000): 14-13.
EndNote Ertaş F (01 Aralık 2000) Correlogram Based Feature Selectıon For Speaker Identıfıcatıon Usıng Vowels. Eskişehir Osmangazi Üniversitesi Mühendislik ve Mimarlık Fakültesi Dergisi 13 2 14–13.
IEEE F. Ertaş, “Correlogram Based Feature Selectıon For Speaker Identıfıcatıon Usıng Vowels”, ESOGÜ Müh Mim Fak Derg, c. 13, sy. 2, ss. 14–13, 2000.
ISNAD Ertaş, Figen. “Correlogram Based Feature Selectıon For Speaker Identıfıcatıon Usıng Vowels”. Eskişehir Osmangazi Üniversitesi Mühendislik ve Mimarlık Fakültesi Dergisi 13/2 (Aralık 2000), 14-13.
JAMA Ertaş F. Correlogram Based Feature Selectıon For Speaker Identıfıcatıon Usıng Vowels. ESOGÜ Müh Mim Fak Derg. 2000;13:14–13.
MLA Ertaş, Figen. “Correlogram Based Feature Selectıon For Speaker Identıfıcatıon Usıng Vowels”. Eskişehir Osmangazi Üniversitesi Mühendislik Ve Mimarlık Fakültesi Dergisi, c. 13, sy. 2, 2000, ss. 14-13.
Vancouver Ertaş F. Correlogram Based Feature Selectıon For Speaker Identıfıcatıon Usıng Vowels. ESOGÜ Müh Mim Fak Derg. 2000;13(2):14-3.

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