activity
20202022
most citedA Full Text-Dependent End to End Mispronunciation Detection and Diagnosis with Easy Data Augmentation Techniques

26 citations · 31 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2022

DialogUSR: Complex Dialogue Utterance Splitting and Reformulation for Multiple Intent Detection

Haoran Meng, Zheng Xin, Tianyu Liu +6

While interacting with chatbots, users may elicit multiple intents in a single dialogue utterance. Instead of training a dedicated multi-intent detection model, we propose DialogUS…

cs.CL20224 cited

Learning Robust Representations for Continual Relation Extraction via Adversarial Class Augmentation

Peiyi Wang, Yifan Song, Tianyu Liu +4

Continual relation extraction (CRE) aims to continually learn new relations from a class-incremental data stream. CRE model usually suffers from catastrophic forgetting problem, i.…

cs.SD2021

Speech Enhancement using Separable Polling Attention and Global Layer Normalization followed with PReLU

Dengfeng Ke, Jinsong Zhang, Yanlu Xie +2

Single channel speech enhancement is a challenging task in speech community. Recently, various neural networks based methods have been applied to speech enhancement. Among these mo…

cs.CL202126 cited

A Full Text-Dependent End to End Mispronunciation Detection and Diagnosis with Easy Data Augmentation Techniques

Kaiqi Fu, Jones Lin, Dengfeng Ke +3

Recently, end-to-end mispronunciation detection and diagnosis (MD&D) systems has become a popular alternative to greatly simplify the model-building process of conventional hybrid…

eess.AS20201 cited

Formant Tracking Using Dilated Convolutional Networks Through Dense Connection with Gating Mechanism

Wang Dai, Jinsong Zhang, Yingming Gao +4

Formant tracking is one of the most fundamental problems in speech processing. Traditionally, formants are estimated using signal processing methods. Recent studies showed that gen…