72 results on '"Md. Sahidullah"'
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2. Graph Neural Networks for Parkinsons Disease Detection.
3. TCG CREST System Description for the Second DISPLACE Challenge.
4. ASVspoof 5: Crowdsourced Speech Data, Deepfakes, and Adversarial Attacks at Scale.
5. Generalizing Speaker Verification for Spoof Awareness in the Embedding Space.
6. ChildAugment: Data Augmentation Methods for Zero-Resource Children's Speaker Verification.
7. Beyond Silence: Bias Analysis through Loss and Asymmetric Approach in Audio Anti-Spoofing.
8. Exploring Green AI for Audio Deepfake Detection.
9. Assessing the Robustness of Spectral Clustering for Deep Speaker Diarization.
10. Modulation spectral features for speech emotion recognition using deep neural networks.
11. Speaker Verification Across Ages: Investigating Deep Speaker Embedding Sensitivity to Age Mismatch in Enrollment and Test Speech.
12. Advancing Stuttering Detection via Data Augmentation, Class-Balanced Loss and Multi-Contextual Deep Learning.
13. Stuttering Detection Using Speaker Representations and Self-supervised Contextual Embeddings.
14. Towards single integrated spoofing-aware speaker verification embeddings.
15. How to Construct Perfect and Worse-than-Coin-Flip Spoofing Countermeasures: A Word of Warning on Shortcut Learning.
16. Distilling Multi-Level X-vector Knowledge for Small-footprint Speaker Verification.
17. Cross-Corpora Spoken Language Identification with Domain Diversification and Generalization.
18. Speaker-Aware Anti-Spoofing.
19. I4U System Description for NIST SRE'20 CTS Challenge.
20. Robust Acoustic Domain Identification with its Application to Speaker Diarization.
21. Learnable Nonlinear Compression for Robust Speaker Verification.
22. Baselines and Protocols for Household Speaker Recognition.
23. Robust Stuttering Detection via Multi-task and Adversarial Learning.
24. End-to-End and Self-Supervised Learning for ComParE 2022 Stuttering Sub-Challenge.
25. ASVspoof 2021: Towards Spoofed and Deepfake Speech Detection in the Wild.
26. Baseline Systems for the First Spoofing-Aware Speaker Verification Challenge: Score and Embedding Fusion.
27. Analysis of constant-Q filterbank based representations for speech emotion recognition.
28. Introducing ECAPA-TDNN and Wav2Vec2.0 Embeddings to Stuttering Detection.
29. An Overview of Indian Spoken Language Recognition from Machine Learning Perspective.
30. Spoofing-Aware Speaker Verification with Unsupervised Domain Adaptation.
31. Machine Learning for Stuttering Identification: Review, Challenges & Future Directions.
32. Non-linear frequency warping using constant-Q transformation for speech emotion recognition.
33. Cross-Corpora Language Recognition: A Preliminary Investigation with Indian Languages.
34. Deep scattering network for speech emotion recognition.
35. Learnable MFCCs for Speaker Verification.
36. Domain-Dependent Speaker Diarization for the Third DIHARD Challenge.
37. Optimizing Multi-Taper Features for Deep Speaker Verification.
38. ABSP System for The Third DIHARD Challenge.
39. Visualizing Classifier Adjacency Relations: A Case Study in Speaker Verification and Voice Anti-Spoofing.
40. Data Generation Using Pass-phrase-dependent Deep Auto-encoders for Text-Dependent Speaker Verification.
41. ASVspoof 2019: spoofing countermeasures for the detection of synthesized, converted and replayed speech.
42. StutterNet: Stuttering Detection Using Time Delay Neural Network.
43. ASVspoof 2021: Automatic Speaker Verification Spoofing and Countermeasures Challenge Evaluation Plan.
44. Optimized Power Normalized Cepstral Coefficients towards Robust Deep Speaker Verification.
45. Benchmarking and challenges in security and privacy for voice biometrics.
46. ASVspoof 2021: accelerating progress in spoofed and deepfake speech detection.
47. Data Quality as Predictor of Voice Anti-Spoofing Generalization.
48. Parameterized Channel Normalization for Far-field Deep Speaker Verification.
49. Utterance partitioning for speaker recognition: an experimental review and analysis with new findings under GMM-SVM framework.
50. A Comparative Re-Assessment of Feature Extractors for Deep Speaker Embeddings.
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