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Effects of Gender Information in Text-Independent and Text-Dependent Speaker Verification
, 2017 It is well-known that for speaker recognition task, gender-dependent acoustic modeling performs better than gender-independent modeling. The practice is to use the gender ground-truth and to train gender-dependent models. However, such information is not
Tomi Kinnunen +2 more
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Text-dependent speaker verification using data fusion
1995 International Conference on Acoustics, Speech, and Signal Processing, 2002A new system is presented for text-dependent speaker verification. The system uses data fusion concepts to combine the results of distortion-based and discriminant-based classifiers. Hence, both intraspeaker and interspeaker information are utilized in the final decision.
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Implementation of text dependent speaker verification on MATLAB
2015 2nd International Conference on Recent Advances in Engineering & Computational Sciences (RAECS), 2015Speech signal carries the information about the linguistic message. Speaker-specific information is also contained in speech signal. No two peoples voice are exactly alike because voice has fingerprint qualities. It is generated by acoustically exciting the cavities of the mouth and nose, and can be used to recognize (identify/verify) a person.
Gurpreet Kaur +3 more
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Text Dependent Speaker Verification With Neural Network
i-manager's Journal on Digital Signal Processing, 2020Speaker recognition system automatically recognizes who the speaker is by using the speaker's speech features included in speech signal. After verifying the speaker claimed to be, it allows and enable access control of various voice services. The main applications of speaker recognition are in the field of forensic and providing additional security ...
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2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018
In this paper, given the speaker bottleneck feature vectors extracted with speaker discriminant neural networks, we focus on using the sequential speaker characteristics for text-dependent speaker verification. In each evaluation trial, speaker supervectors are used as the representations of the sequential speaker characteristics rendered in the ...
Liping Chen +5 more
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In this paper, given the speaker bottleneck feature vectors extracted with speaker discriminant neural networks, we focus on using the sequential speaker characteristics for text-dependent speaker verification. In each evaluation trial, speaker supervectors are used as the representations of the sequential speaker characteristics rendered in the ...
Liping Chen +5 more
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Covariance Based Deep Feature for Text-Dependent Speaker Verification
Lecture Notes in Computer Science, 2018d-vector approach achieved impressive results in speaker verification. Representation is obtained at utterance level by calculating the mean of the frame level outputs of a hidden layer of the DNN. Although mean based speaker identity representation has achieved good performance, it ignores the variability of frames across the whole utterance, which ...
Yanmin Qian, Kai Yu, Shuai Wang
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Text-dependent Speaker Verification Using Word-based Scoring
2018 11th International Symposium on Chinese Spoken Language Processing (ISCSLP), 2018As the separated modeling methods are widely used in text-dependent speaker verification task. The reason why they are so effective is discussed in this paper. A word-based scoring method is then proposed based on our discussion. Specifically, a segmentation algorithm is firstly used for segmenting the enrollment and test utterances into words ...
Shengyu Yao +3 more
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Parallel Speaker and Content Modelling for Text-Dependent Speaker Verification
Interspeech 2016, 2016Jianbo Ma +4 more
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HiLAM-Aligned Kernel Discriminant Analysis for Text-Dependent Speaker Verification
Expert Systems With Applications, 2021Azharuddin Laskar, Rabul Hussain Laskar
exaly
Multi-task learning for text-dependent speaker verification
Interspeech 2015, 2015Nanxin Chen, Yanmin Qian, Kai Yu 0004
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