Text-Independent Speaker Verification
17 papers with code • 0 benchmarks • 0 datasets
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Asymmetric and trial-dependent modeling: the contribution of LIA to SdSV Challenge Task 2
The SdSv challenge Task 2 provided an opportunity to assess efficiency and robustness of modern text-independent speaker verification systems.
Enhancement of a Text-Independent Speaker Verification System by using Feature Combination and Parallel-Structure Classifiers
In this work, we propose the combination of two SVM-based classifiers with different kernel functions: Linear kernel and Gaussian Radial Basis Function (RBF) kernel with a Logistic Regression (LR) classifier.
VoiceExtender: Short-utterance Text-independent Speaker Verification with Guided Diffusion Model
Speaker verification (SV) performance deteriorates as utterances become shorter.
Model Compression for DNN-based Speaker Verification Using Weight Quantization
Experimental results on VoxCeleb show that weight quantization is effective for compressing SV models.
Convolution-Based Channel-Frequency Attention for Text-Independent Speaker Verification
The weights are imposed on the input features to improve the representation ability for speaker modeling.
Attention-based conditioning methods using variable frame rate for style-robust speaker verification
However, self-attentive embeddings perform weighted pooling such that the weights correspond to the importance of the frames in a speaker classification task.
SuperVoice: Text-Independent Speaker Verification Using Ultrasound Energy in Human Speech
Our evaluation shows that SUPERVOICE achieves 0. 58% equal error rate in the speaker verification task, it only takes 120 ms for testing an incoming utterance, outperforming all existing speaker verification systems.
MFA: TDNN with Multi-scale Frequency-channel Attention for Text-independent Speaker Verification with Short Utterances
The time delay neural network (TDNN) represents one of the state-of-the-art of neural solutions to text-independent speaker verification.
Impact of Naturalistic Field Acoustic Environments on Forensic Text-independent Speaker Verification System
Audio analysis for forensic speaker verification offers unique challenges in system performance due in part to data collected in naturalistic field acoustic environments where location/scenario uncertainty is common in the forensic data collection process.
Novel Hybrid DNN Approaches for Speaker Verification in Emotional and Stressful Talking Environments
The test results of the aforementioned hybrid models demonstrated that the proposed HMM-DNN leveraged the verification performance in emotional and stressful environments.
