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Robust Speaker Identification and Verification
IEEE Computational Intelligence Magazine, 2007Acoustic characteristics have played an essential role in biometrics. In this article, we introduce a robust, text-independent speaker identification/verification system. This system is mainly based on a subspace-based enhancement technique and probabilistic support vector machines (SVMs).
Jia-Ching Wang +3 more
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Efficient speaker identification and retrieval
Interspeech 2005, 2005In this paper we present techniques for efficient speaker recognition of a large population of speakers and for efficient speaker retrieval in large audio archives. We deal with aspects of both time and storage. We use Gaussian mixture modeling (GMM) for representing both train and test sessions and show how to perform speaker recognition and retrieval
Hagai Aronowitz, David Burshtein
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Identification of speakers engaged in dialog
IEEE International Conference on Acoustics Speech and Signal Processing, 1993The approach developed is based on the robust evaluation of likelihoods based on speech segments. The method shows that speakers can be identified with minimal loss of performance in the presence of large amounts of undesired speech. The authors consider the case where there are models for only one of the two speakers and the case where one is ...
George Yu, Herbert Gish
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Microphone arrays and speaker identification
IEEE Transactions on Speech and Audio Processing, 1994Hands-free operation of speech processing equipment is sometimes desired so that the user is unencumbered by hand-held or body-worn microphones. This paper explores the use of array microphones to capture speech under adverse acoustic conditions, and provide input to a system for automatic speaker identification.
Qiguang Lin +2 more
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Text-independent speaker identification
IEEE Signal Processing Magazine, 1994We describe current approaches to text-independent speaker identification based on probabilistic modeling techniques. The probabilistic approaches have largely supplanted methods based on comparisons of long-term feature averages. The probabilistic approaches have an important and basic dichotomy into nonparametric and parametric probability models ...
Herbert Gish, Michael Schmidt 0008
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Large-scale speaker identification
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014Speaker identification is one of the main tasks in speech processing. In addition to identification accuracy, large-scale applications of speaker identification give rise to another challenge: fast search in the database of speakers. In this paper, we propose a system based on i-vectors, a current approach for speaker identification, and locality ...
Ludwig Schmidt +2 more
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Speaker Identification in a Multi-speaker Environment
2017Human beings are capable of performing unfathomable tasks. A human being is able to focus on a single person’s voice in an environment of simultaneous conversations. We have tried to emulate this particular skill through an artificial intelligence system.
Manthan Thakker +3 more
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Live speaker identification in conversations
Proceedings of the 16th ACM international conference on Multimedia, 2008The following article describes our technical demonstration of an online speaker identification system for conversations. A laptop with an internal microphone is centrally placed in the table of a meeting room. The system is able to identify the current speaker independent of spoken text or language with a latency of about 1.5 seconds and an accuracy ...
Gerald Friedland, Oriol Vinyals
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Text-independent speaker identification
1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings, 2002We have developed a new approach for speaker identification (SID) that employs fenonic speaker Markov modeling (FSMM). The FSMM is a hidden Markov model whose parameters capture and describe intra-speaker spectral dynamics. FSMM technology has been successfully applied in isolated word recognition and speaker adaptation applications.
Martha Birnbaum +2 more
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Signal modeling for speaker identification
1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings, 2002A large number of parameters, including pitch, LPCC, /spl Delta/LPCC, PARCOR, MFCC, /spl Delta/MFCC, and residual cepstrum (RCEP) were extracted from speech signals and their effectiveness for text-independent speaker identification was evaluated. In addition, the usefulness of two signal processing techniques, preemphasis and cepstral weighting, was ...
Li Liu 0008, Jialong He, Günther Palm
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