research
∙
03/07/2022
A study on joint modeling and data augmentation of multi-modalities for audio-visual scene classification
In this paper, we propose two techniques, namely joint modeling and data...
share
research
∙
10/16/2021
A Variational Bayesian Approach to Learning Latent Variables for Acoustic Knowledge Transfer
We propose a variational Bayesian (VB) approach to learning distribution...
research
∙
10/08/2021
A Study of Low-Resource Speech Commands Recognition based on Adversarial Reprogramming
In this study, we propose a novel adversarial reprogramming (AR) approac...
research
∙
07/03/2021
A Lottery Ticket Hypothesis Framework for Low-Complexity Device-Robust Neural Acoustic Scene Classification
We propose a novel neural model compression strategy combining data augm...
research
∙
12/14/2020
REDAT: Accent-Invariant Representation for End-to-End ASR by Domain Adversarial Training with Relabeling
Accents mismatching is a critical problem for end-to-end ASR. This paper...
research
∙
11/03/2020
A Two-Stage Approach to Device-Robust Acoustic Scene Classification
To improve device robustness, a highly desirable key feature of a compet...
research
∙
07/31/2020
Relational Teacher Student Learning with Neural Label Embedding for Device Adaptation in Acoustic Scene Classification
In this paper, we propose a domain adaptation framework to address the d...
research
∙
07/31/2020
An Acoustic Segment Model Based Segment Unit Selection Approach to Acoustic Scene Classification with Partial Utterances
In this paper, we propose a sub-utterance unit selection framework to re...
research
∙
07/25/2020
Exploring Deep Hybrid Tensor-to-Vector Network Architectures for Regression Based Speech Enhancement
This paper investigates different trade-offs between the number of model...
research
∙
07/16/2020
Device-Robust Acoustic Scene Classification Based on Two-Stage Categorization and Data Augmentation
In this technical report, we present a joint effort of four groups, name...
research
∙
05/01/2020
Exploring Pre-training with Alignments for RNN Transducer based End-to-End Speech Recognition
Recently, the recurrent neural network transducer (RNN-T) architecture h...
research
∙
04/25/2020
L-Vector: Neural Label Embedding for Domain Adaptation
We propose a novel neural label embedding (NLE) scheme for the domain ad...
research
∙
02/03/2020
Tensor-to-Vector Regression for Multi-channel Speech Enhancement based on Tensor-Train Network
We propose a tensor-to-vector regression approach to multi-channel speec...
research
∙
09/26/2019