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Found 5 papers, 1 papers with code
Tailoring Self-Supervision for Supervised Learning
Our exhaustive experiments validate the merits of LoRot as a pretext task tailored for supervised learning in terms of robustness and generalization capability.
Ranked #9 on
Data Augmentation
on ImageNet
Self-Attentive Multi-Layer Aggregation with Feature Recalibration and Normalization for End-to-End Speaker Verification System
Therefore, we propose a self-attentive multi-layer aggregation with feature recalibration and normalization for end-to-end speaker verification system.
MCSAE: Masked Cross Self-Attentive Encoding for Speaker Embedding
Based on multi-layer aggregation, the output features of each residual layer are used for the MCSAE.
Integration of TensorFlow based Acoustic Model with Kaldi WFST Decoder
By contrast, a general-purpose deep learning framework, such as TensorFlow, can easily build various types of neural network architectures using a tensor-based computation method, but it is difficult to apply them to WFST-based speech recognition.
A Fast-Converged Acoustic Modeling for Korean Speech Recognition: A Preliminary Study on Time Delay Neural Network
In this paper, a time delay neural network (TDNN) based acoustic model is proposed to implement a fast-converged acoustic modeling for Korean speech recognition.
