Search Results for author:
Found 12 papers, 4 papers with code
A Glance is Enough: Extract Target Sentence By Looking at A keyword
This paper investigates the possibility of extracting a target sentence from multi-talker speech using only a keyword as input.
Spot keywords from very noisy and mixed speech
We propose a novel Mix Training (MT) strategy that encourages the model to discover low-energy keywords from noisy and mixed speech.
Time-weighted Frequency Domain Audio Representation with GMM Estimator for Anomalous Sound Detection
This paper presents Time-Weighted Frequency Domain Representation (TWFR) with the GMM method (TWFR-GMM) for anomalous sound detection.
Using Auxiliary Tasks In Multimodal Fusion Of Wav2vec 2.0 And BERT For Multimodal Emotion Recognition
For the difficulty of multimodal fusion, we use a K-layer multi-head attention mechanism as a downstream fusion module.
Exploring Transformer's potential on automatic piano transcription
Most recent research about automatic music transcription (AMT) uses convolutional neural networks and recurrent neural networks to model the mapping from music signals to symbolic notation.
Can We Trust Deep Speech Prior?
Recently, speech enhancement (SE) based on deep speech prior has attracted much attention, such as the variational auto-encoder with non-negative matrix factorization (VAE-NMF) architecture.
Speech Separation Based on Multi-Stage Elaborated Dual-Path Deep BiLSTM with Auxiliary Identity Loss
We have open sourced our re-implementation of the DPRNN-TasNet here (https://github. com/ShiZiqiang/dual-path-RNNs-DPRNNs-based-speech-separation), and our TasTas is realized based on this implementation of DPRNN-TasNet, it is believed that the results in this paper can be reproduced with ease.
La Furca: Iterative Context-Aware End-to-End Monaural Speech Separation Based on Dual-Path Deep Parallel Inter-Intra Bi-LSTM with Attention
We have open-sourced our re-implementation of the DPRNN-TasNet in https://github. com/ShiZiqiang/dual-path-RNNs-DPRNNs-based-speech-separation, and our `La Furca' is realized based on this implementation of DPRNN-TasNet, it is believed that the results in this paper can be smoothly reproduced.
Sound Audio and Speech Processing
Hard Sample Mining for the Improved Retraining of Automatic Speech Recognition
Thus, the parameters are more influenced by the training samples with a big propagation error than the samples with a small one.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
A Multi-Task Learning Framework for Overcoming the Catastrophic Forgetting in Automatic Speech Recognition
On the one hand, we constrain the new parameters not to deviate too far from the original parameters and punish the new system when forgetting original knowledge.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Acoustic Scene Classification by Implicitly Identifying Distinct Sound Events
In this paper, we propose a new strategy for acoustic scene classification (ASC) , namely recognizing acoustic scenes through identifying distinct sound events.
FurcaNeXt: End-to-end monaural speech separation with dynamic gated dilated temporal convolutional networks
Deep dilated temporal convolutional networks (TCN) have been proved to be very effective in sequence modeling.
Sound Audio and Speech Processing
