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On the use of speaker superfactors for speaker recognition

2010 IEEE International Conference on Acoustics, Speech and Signal Processing, 2010
We propose a new method to characterize a speaker within the Joint Factor Analysis (JFA) framework. Scoring within the JFA framework can be costly and a new method was proposed to produce an accurate score in a fast manner. However, this method is nonsymmetric and performs badly without any score normalization.
Scheffer, Nicholas, Vogt, Robert
openaire   +2 more sources

Pitch in Speaker Recognition

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
openaire   +1 more source

Familiar speaker recognition

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
openaire   +1 more source

Speaker Recognition

The Application of Artificial Intelligence, 2000
Homayoon Beigi
openaire   +2 more sources

Reshape Dimensions Network for Speaker Recognition

Interspeech
In this paper, we present Reshape Dimensions Network (ReDimNet), a novel neural network architecture for extracting utterance-level speaker representations.
Ivan Yakovlev   +5 more
semanticscholar   +1 more source

Distributed speaker recognition

Interspeech 2004, 2004
Speech 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
openaire   +1 more source

Speaker recognition and speaker normalization by projection to speaker subspace

1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings, 2002
An 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
openaire   +1 more source

Graph-embedding for speaker recognition

Interspeech 2010, 2010
This 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
openaire   +1 more source

Fusing MFCC and LPC Features Using 1D Triplet CNN for Speaker Recognition in Severely Degraded Audio Signals

IEEE Transactions on Information Forensics and Security, 2020
Speaker recognition algorithms are negatively impacted by the quality of the input speech signal. In this work, we approach the problem of speaker recognition from severely degraded audio data by judiciously combining two commonly used features: Mel ...
Anurag Chowdhury, A. Ross
semanticscholar   +1 more source

Speaker recognition in conjunction with speaker independent word recognition

The Journal of the Acoustical Society of America, 1980
Our 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
openaire   +1 more source

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