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Found 6 papers, 1 papers with code
Improving Transformer-based End-to-End Speaker Diarization by Assigning Auxiliary Losses to Attention Heads
In this study, to enhance the training effectiveness of SA-EEND models, we propose the use of auxiliary losses for the SA heads of the transformer layers.
Task-specific Optimization of Virtual Channel Linear Prediction-based Speech Dereverberation Front-End for Far-Field Speaker Verification
Developing a single-microphone speech denoising or dereverberation front-end for robust automatic speaker verification (ASV) in noisy far-field speaking scenarios is challenging.
Knowledge distillation from language model to acoustic model: a hierarchical multi-task learning approach
The remarkable performance of the pre-trained language model (LM) using self-supervised learning has led to a major paradigm shift in the study of natural language processing.
Attribution Mask: Filtering Out Irrelevant Features By Recursively Focusing Attention on Inputs of DNNs
In this study, we use the attributions that filter out irrelevant parts of the input features and then verify the effectiveness of this approach by measuring the classification accuracy of a pre-trained DNN.
Attention Wave-U-Net for Acoustic Echo Cancellation
In this paper, a Wave-U-Net based acoustic echo cancellation (AEC) with an attention mechanism is proposed to jointly sup- press acoustic echo and background noise.
Ensemble of Jointly Trained Deep Neural Network-Based Acoustic Models for Reverberant Speech Recognition
Distant speech recognition is a challenge, particularly due to the corruption of speech signals by reverberation caused by large distances between the speaker and microphone.
