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speaker identification

Fast training of Large Margin diagonal Gaussian mixture models for speaker identification

Fast training of Large Margin diagonal Gaussian mixture models for speaker identification

... V. C ONCLUSION We presented a new simplified algorithm to train Large- Margin GMM by using the k-best scoring Gaussians selected form the UBM. This algorithm is highly efficient which makes it well suited to process ...

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Speaker identification by computer and human evaluated on the SPIDRE corpus

Speaker identification by computer and human evaluated on the SPIDRE corpus

... The selection o f ten females has been based on pitch frequency dis­ tribution. They have a similar distribution o f pitch. We already found that based on the pitch, the task was tedious for computers w hen using ...

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Deep complementary features for speaker identification in TV broadcast data

Deep complementary features for speaker identification in TV broadcast data

... 1. Introduction In the past few years, Convolutional Neural Networks (CNN) became widely used in image related domains providing state- of-the-art performance [1]. At the same time Deep Neural Net- works (DNN) were being ...

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Combination of SVM and Large Margin GMM modeling for speaker identification

Combination of SVM and Large Margin GMM modeling for speaker identification

... state-of-the-art speaker recognition systems are partially or completely based on Gaussian mixture models ...in speaker recognition during the last ...of speaker identification. We carry out a ...

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Person Instance Graphs for Named Speaker Identification in TV Broadcast

Person Instance Graphs for Named Speaker Identification in TV Broadcast

... the speaker themselves, the ad- dressee or someone ...with speaker turns ...overall speaker identification performance ...that identification error rates increase from 17% up to 75% ...

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Unsupervised Speaker Identification in TV Broadcast Based on Written Names

Unsupervised Speaker Identification in TV Broadcast Based on Written Names

... current speaker, identification of speech turns via the ILP solver corresponded to find the less expensive way to connect names and speech ...of identification results obtained with this method and ...

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Supervised Group Nonnegative Matrix Factorisation With Similarity Constraints And Applications To Speaker Identification

Supervised Group Nonnegative Matrix Factorisation With Similarity Constraints And Applications To Speaker Identification

... 5. EXPERIMENTS 5.1. Corpus The approach presented here is evaluated on a subset of ESTER, a corpus for automatic speech recognition composed of data recorded from broadcast radio [19]. The subset of ESTER is composed of ...

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Group Non-Negative Matrix Factorisation With Speaker And Session Similarity Constraints For Speaker Identification

Group Non-Negative Matrix Factorisation With Speaker And Session Similarity Constraints For Speaker Identification

... retrieve speaker iden- ...the speaker identity [10]. Using speaker identity to induce group sparsity or groups similarity has then proven to improve further the performance of NMF- based approaches ...

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Speech and Speaker Recognition for Home Automation: Preliminary Results

Speech and Speaker Recognition for Home Automation: Preliminary Results

... and speaker identification systems face distance speech conditions which have a significant impact on ...For speaker identification, the performances were below very speaker ...

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A language-familiarity effect for speaker discrimination without comprehension

A language-familiarity effect for speaker discrimination without comprehension

... upon speaker identification is well established, to such an extent that it has been argued that “Human voice recognition depends on language ability” [Perrachione TK, Del Tufo SN, Gabrieli JDE (2011) ...

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Towards multiple vocal effort speaker verification:
exploring speaker-dependent invariant information
between normal and whispered speech.

Towards multiple vocal effort speaker verification: exploring speaker-dependent invariant information between normal and whispered speech.

... example, speaker identification accuracy as low as 7% have been reported in very noisy envi- ronments ...environment-robust speaker recognition applications ...on speaker verification ...

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Speaker verification using Large Margin GMM discriminative training

Speaker verification using Large Margin GMM discriminative training

... Fig. 1. DET plots for GMM and LM-dGMM systems with T-normalization. of EER of about 4.87%. These results suggest that our k-best technique not only allow efficient training but also still outperforms the baseline ...

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Speaker Identication Using Discriminative Learning of Large Margin GMM

Speaker Identication Using Discriminative Learning of Large Margin GMM

... In order to address this problem, we propose in this paper a new approach for fast training of Large-Margin GMM which allow efficient processing in large scale applications. To do so, we exploit the fact that in general ...

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Speaker information modification in the VoicePrivacy 2020 toolchain

Speaker information modification in the VoicePrivacy 2020 toolchain

... more speaker-invariant or speaker-independent [10, ...the speaker identity has not been ...the speaker identification classification ...the speaker verification ...

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Large Margin GMM for discriminative speaker verifi cation

Large Margin GMM for discriminative speaker verifi cation

... Following the same philosophy of traditional GMM, we proposed in [12] to neglect the orientation of the covariance matrices in training. We showed in [12] that the resulting simplified algorithm has the advantage of ...

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Recent Improvements on ILP-based Clustering for Broadcast News Speaker Diarization

Recent Improvements on ILP-based Clustering for Broadcast News Speaker Diarization

... 3.1. HAC clustering with GMMs In this clustering stage, speakers are processed separately ac- cording to the gender previously detected. Speakers can now be modeled with GMMs, thanks to the high purity clustering ...

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A text-independent speaker authentication system for mobile devices

A text-independent speaker authentication system for mobile devices

... proposed speaker recognition and identification systems achieve accurate results [ 18 – 22 ...independent Speaker Authentication (TiSA) system suitable for mobile devices while focusing on ...

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SLOGD: Speaker Location Guided Deflation Approach to Speech Separation

SLOGD: Speaker Location Guided Deflation Approach to Speech Separation

... 3. EXPERIMENTAL SETTINGS 3.1. Dataset Experiments are conducted on the multichannel, reverberated, noisy version of the WSJ-2MIX dataset [1] introduced in [10]. Each mixture was generated by convolving two clean Wall ...

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Tandem Assessment of Spoofing Countermeasures and Automatic Speaker Verification: Fundamentals

Tandem Assessment of Spoofing Countermeasures and Automatic Speaker Verification: Fundamentals

... Junichi Yamagishi, Senior Member, IEEE, and Douglas A. Reynolds, Fellow, IEEE, Abstract—Recent years have seen growing efforts to develop spoofing countermeasures (CMs) to protect automatic speaker verification ...

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When pitch accents encode speaker commitment: evidence from French intonation

When pitch accents encode speaker commitment: evidence from French intonation

... encodes speaker commitment in French yes-no ...the speaker is not biased toward the answer he/she expects, and the H+!H* pitch accent signals that the speaker believes the proposition to be ...encode ...

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