173 results on '"Driss Matrouf"'
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2. Attention-based Comparison on Aligned Utterances for Text-Dependent Speaker Verification.
3. Spoofing detection in the wild: an investigation of approaches to improve generalisation.
4. Hiding Speaker's Sex in Speech Using Zero-Evidence Speaker Representation in an Analysis/Synthesis Pipeline.
5. Barlow Twins self-supervised learning for robust speaker recognition.
6. A Comprehensive Exploration of Noise Robustness and Noise Compensation in ResNet and TDNN-based Speaker Recognition Systems.
7. Learning Noise Robust ResNet-Based Speaker Embedding for Speaker Recognition.
8. A Bridge between Features and Evidence for Binary Attribute-Driven Perfect Privacy.
9. Joint Optimization of Diffusion Probabilistic-Based Multichannel Speech Enhancement with Far-Field Speaker Verification.
10. Adversarial Disentanglement of Speaker Representation for Attribute-Driven Privacy Preservation.
11. Compensate multiple distortions for speaker recognition systems.
12. Language Adaptation for Speaker Recognition Systems Using Contrastive Learning.
13. Speech Pseudonymisation Assessment Using Voice Similarity Matrices.
14. Data augmentation versus noise compensation for x-vector speaker recognition systems in noisy environments.
15. Denoising x-vectors for Robust Speaker Recognition.
16. How to Leverage DNN-based speech enhancement for multi-channel speaker verification?
17. Hiding speaker's sex in speech using zero-evidence speaker representation in an analysis/synthesis pipeline.
18. A bridge between features and evidence for binary attribute-driven perfect privacy.
19. Preserving privacy in speaker and speech characterisation.
20. Towards a unified assessment framework of speech pseudonymisation.
21. The I4U Mega Fusion and Collaboration for NIST Speaker Recognition Evaluation 2016.
22. A Unified Joint Model to Deal With Nuisance Variabilities in the i-Vector Space.
23. Adversarial Disentanglement of Speaker Representation for Attribute-Driven Privacy Preservation.
24. Probabilistic Approach Using Joint Long and Short Session i-Vectors Modeling to Deal with Short Utterances for Speaker Recognition.
25. LIA System for the SITW Speaker Recognition Challenge.
26. Probabilistic Approach Using Joint Clean and Noisy i-Vectors Modeling for Speaker Recognition.
27. Iterative Bayesian and MMSE-based noise compensation techniques for speaker recognition in the i-vector space.
28. Local binary patterns as features for speaker recognition.
29. Fast i-vector denoising using MAP estimation and a noise distributions database for robust speaker recognition.
30. A comparison of normalization techniques applied to latent space representations for speech analytics.
31. Dealing with additive noise in speaker recognition systems based on i-vector approach.
32. Additive noise compensation in the i-vector space for speaker recognition.
33. The ASVspoof 2019 database.
34. A study on the roles of total variability space and session variability modeling in speaker recognition.
35. An I-vector Based Approach to Compact Multi-Granularity Topic Spaces Representation of Textual Documents.
36. I-vector based representation of highly imperfect automatic transcriptions.
37. Factor analysis based semantic variability compensation for automatic conversation representation.
38. Subspace Gaussian mixture models for dialogues classification.
39. Exploring some limits of Gaussian PLDA modeling for i-vector distributions.
40. Robust Speaker Recognition Using MAP Estimation of Additive Noise in i-vectors Space.
41. I4u submission to NIST SRE 2012: a large-scale collaborative effort for noise-robust speaker verification.
42. Identify the Benefits of the Different Steps in an i-Vector Based Speaker Verification System.
43. Bi-Modal Person Recognition on a Mobile Phone: Using Mobile Phone Data.
44. Study of the Effect of I-vector Modeling on Short and Mismatch Utterance Duration for Speaker Verification.
45. Subspace Gaussian Mixture Models Based on Noise Compensation for Speech Recognition.
46. Analyse en Composante Principale pour l'extraction des i-vecteurs en vérification du locuteur (Principal Component Analysis for i-vector extraction in speaker verification.) [in French].
47. Speaker verification using m-vector extracted from MLLR super-vector.
48. Variance-spectra based normalization for i-vector standard and probabilistic linear discriminant analysis.
49. I-vectors in the context of phonetically-constrained short utterances for speaker verification.
50. Acoustic modeling for under-resourced languages based on vectorial HMM-states representation using Subspace Gaussian Mixture Models.
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