Sentence‐HMM state‐based i‐vector/PLDA modelling for improved performance in text dependent single utterance speaker verification

Author:

Büyük Osman1

Affiliation:

1. Electronics and Telecommunications Engineering DepartmentKocaeli UniversityKocaeli41380Turkey

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Signal Processing

Reference33 articles.

1. National Institute of Standards and Technology: ‘Speaker recognition evaluation’. Available athttp://www.nist.gov/speech/tests/spkaccessed September 2015

2. Nealand J.H. Pelecanos J.W. Zilca R.D.et al: ‘Study of the relative importance of temporal characteristics in text‐dependent and text‐constrained speaker verification’.Proc. IEEE Int. Conf. on Acoustics Speech and Signal Processing 2005 (ICASSP 2005) Philadelphia USA vol.1 pp.653–656

3. Reynolds D.A.: ‘Channel robust speaker verification via feature mapping’.Proc. IEEE Int. Conf. on Acoustics Speech and Signal Processing 2003 (ICASSP 2003) Hong Kong vol.2 p. II‐53‐6

4. Zhu D. Ma B. Li H.et al: ‘A generalized feature transformation approach for channel robust speaker verification’.Proc. IEEE Int. Conf. on Acoustics Speech and Signal Processing (ICASSP 2007) Honolulu Hawaii USA 2007 vol.4 pp.61–64

5. Teunen R. Shahshahani B. Heck L.P.: ‘A model‐based transformational approach to robust speaker recognition’.Proc. Int. Conf. on Spoken Language Processing (ICSLP 2000) Beijing China 2000 vol.2 pp.495–498

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