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Found 7 papers, 0 papers with code
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.
Learning from human perception to improve automatic speaker verification in style-mismatched conditions
Using the SITW evaluation tasks, which involve different conversational speech tasks, the proposed loss combined with self-attention conditioning results in significant relative improvements in EER by 2-5% and minDCF by 6-12% over baseline.
Sequence-level Confidence Classifier for ASR Utterance Accuracy and Application to Acoustic Models
We propose a cost-effective method of using CC scores to select an optimal adaptation data set, where we maximize ASR gains from minimal data.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Bi-APC: Bidirectional Autoregressive Predictive Coding for Unsupervised Pre-training and Its Application to Children's ASR
We present a bidirectional unsupervised model pre-training (UPT) method and apply it to children's automatic speech recognition (ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Variable frame rate-based data augmentation to handle speaking-style variability for automatic speaker verification
For instance, when enrolled with conversation utterances, the EER increased to 3. 03%, 2. 96% and 22. 12% when tested on read, narrative, and pet-directed speech, respectively.
Speaker discrimination in humans and machines: Effects of speaking style variability
Native listeners performed better than machines in the style-matched conditions (EERs of 6. 96% versus 14. 35% for read speech, and 15. 12% versus 19. 87%, for conversations), but for style-mismatched conditions, there was no significant difference between native listeners and machines.
Exploring the Use of an Unsupervised Autoregressive Model as a Shared Encoder for Text-Dependent Speaker Verification
A fusion of the x-vector/PLDA baseline and the SID/PLDA scores prior to PID fusion further improved performance by 15% indicating complementarity of the proposed approach to the x-vector system.
