Results 271 to 280 of about 54,457 (305)

Dimension Compactness in Speaker Identification

Proceedings of the International Conference on Informatics and Analytics, 2016
The automatic speaker identification procedure is used to extract features that help to identify the components of the acoustic signal by discarding all the other stuff like background noise, emotion, hesitation, etc. The acoustic signal is generated by a human that is filtered by the shape of the vocal tract, including tongue, teeth, etc. The shape of
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Wavelet-based speaker identification

2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No.02TH8628), 2003
We propose a new way of speaker identification based on wavelets and hidden Markov models. We introduce multi-stream hidden Markov model and show the results of speaker identification experiment.
Evgeny I. Bovbel, Igor E. Kheidorov, Y. A. Chaikou   +2 more
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Real-time speaker identification

Interspeech 2004, 2004
In speaker identification, most of the computation originates from distance or likelihood computations between the feature vectors of the unknown speaker and the models in the database. The identification time depends on the number of feature vectors, their dimensionality, the complexity of the speaker models and the number of speakers.
Pasi Fränti, Evgeny Karpov, Tomi Kinnunen   +2 more
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Speech Enhancement for Speaker Identification

2018 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT), 2018
This paper presents a algorithm for speech enhancement and speaker identification. Discrete-wavelet transform (DWT) based algorithm are used for speech enhancement. In this a Five level discrete wavelet decomposition is used and all the five level output are given as input to the binary mask thresholding function to enhance the speech patterns.
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Dereverberation for Speaker Identification in Meeting

2014
Current state-of-the-art speaker identification is a well-established research problem but reverberation is still a major issue used in real meeting scenarios. Dereverberation is essential for many applications such as speaker identification and speech recognition to improve the quality and intelligibility of speech signal interrupted by real ...
Yi Yang 0039, Jia Liu 0001
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Identification of Speakers from Their Hum

2008
Automatic Speaker Recognition (ASR)is an economic method of biometrics because of the availability of low cost and powerful processors. An ASR system will be efficient if the proper speaker-specificfeatures are extracted. Most of the state-of-the-art ASR systems use the natural speech signal (either read speech or spontaneous speech) from the subjects.
Hemant A. Patil, Robin Jain, Prakhar Kant Jain   +2 more
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Speaker's identification by voice

First European Conference on Speech Communication and Technology (Eurospeech 1989), 1989
Antonella Giannini, Massimo Pettorino, Umberto Cinque   +2 more
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Confidence metrics for speaker identification

7th International Conference on Spoken Language Processing (ICSLP 2002), 2002
Mark C. Huggins, John J. Grieco
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The prototype model in speaker identification

6th European Conference on Speech Communication and Technology, 1999
Yizhar Lavner, Judith Rosenhouse, Isak Gath   +2 more
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Improving speaker de-identification with functional data analysis of f0 trajectories

Speech Communication, 2022
Lauri Tavi, Tomi Kinnunen, Rosa Gonzalez Hautamäki   +2 more
exaly