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2009 Ninth International Conference on Hybrid Intelligent Systems, 2009
In order to improve the speaker recognition accuracy, the pitch is applied to GMM-based speaker recognition (SR). The circular average magnitude difference function (CAMDF) method is used to extract the pitch. An endpoint detection method based on the pitch is proposed.
Jian-wei Zhu +3 more
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In order to improve the speaker recognition accuracy, the pitch is applied to GMM-based speaker recognition (SR). The circular average magnitude difference function (CAMDF) method is used to extract the pitch. An endpoint detection method based on the pitch is proposed.
Jian-wei Zhu +3 more
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2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012
Speaker recognition by machines can be quite good for large groups as seen in NIST speaker recognition evaluations. However, speaker recognition by machine can be fragile for changing environments. This research examines how robust humans are for recognizing familiar speakers in changing environments.
Stanley J. Wenndt, Ronald L. Mitchell
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Speaker recognition by machines can be quite good for large groups as seen in NIST speaker recognition evaluations. However, speaker recognition by machine can be fragile for changing environments. This research examines how robust humans are for recognizing familiar speakers in changing environments.
Stanley J. Wenndt, Ronald L. Mitchell
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Distributed speaker recognition
Interspeech 2004, 2004Speech recognition systems are gaining increasing importance with the wide-spread use of mobile and portable devices and other interactive voice response systems. Because of the resource constraints on such devices and the requirements of specific applications, the need to perform speech recognition over a data network becomes inevitable.
Veena Desai, Hema A. Murthy
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Speaker recognition and speaker normalization by projection to speaker subspace
1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings, 2002An individual speaker is thought to have his own subspace in which his phonetic information is included. However, conventional speaker-independent HMMs ignore the speaker subspaces and gather speech data spread widely in the observation space. Then they cause probability distribution flatness of HMMs and the resultant recognition errors.
Yasuo Ariki +2 more
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Graph-embedding for speaker recognition
Interspeech 2010, 2010This chapter presents applications of graph embedding to the problem of text-independent speaker recognition. Speaker recognition is a general term encompassing multiple applications. At the core is the problem of speaker comparison—given two speech recordings (utterances), produce a score which measures speaker similarity.
Zahi N. Karam, William M. Campbell
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Speaker recognition in conjunction with speaker independent word recognition
The Journal of the Acoustical Society of America, 1980Our method for accomplishing speaker independent word recognition is to select a small set of word templates that typify and span individual speaker reference templates obtained from a large population of speakers. An unknown utterance is processed and compared with a set of such templates for each word in the vocabulary.
A. E. Rosenberg, K. L. Shipley
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Constrained MLLR for Speaker Recognition
2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07, 2007abstract
Ferras, Marc +3 more
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From Speaker Recognition to Forensic Speaker Recognition
2014The goal of this paper is to review automatic systems for forensic speaker recognition (FSR) based on scientifically approved methods for calculation and interpretation of biometric evidence. The objective of this paper is not to promote one speaker recognition method against another, but is to make available to the biometric research community data ...
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Speaker recognition in a multi-speaker environment
7th European Conference on Speech Communication and Technology (Eurospeech 2001), 2001Alvin F. Martin, Mark A. Przybocki
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4th European Conference on Speech Communication and Technology (Eurospeech 1995), 1995
Kin Yu, John S. Mason, John Oglesby
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Kin Yu, John S. Mason, John Oglesby
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