Zhengkun Tian | DeepAI

AI Chat

Featured Co-authors

PetsTime
196 publications
Haizhou Li
150 publications
Bin Liu
139 publications
Shuai Zhang
100 publications
Jianhua Tao
77 publications
Jiangyan Yi
50 publications
Chenglong Wang
47 publications
Min Li
44 publications
Xiaohui Zhang
33 publications
Zhengqi Wen
30 publications
Zheng Lian
24 publications

∙ 07/17/2023

TST: Time-Sparse Transducer for Automatic Speech Recognition

End-to-end model, especially Recurrent Neural Network Transducer (RNN-T)...

0 Xiaohui Zhang, et al. ∙

∙ 11/11/2022

SceneFake: An Initial Dataset and Benchmarks for Scene Fake Audio Detection

Previous databases have been designed to further the development of fake...

0 Jiangyan Yi, et al. ∙

∙ 11/07/2022

Peak-First CTC: Reducing the Peak Latency of CTC Models by Applying Peak-First Regularization

The CTC model has been widely applied to many application scenarios beca...

0 Zhengkun Tian, et al. ∙

∙ 08/21/2022

System Fingerprints Detection for DeepFake Audio: An Initial Dataset and Investigation

Many effective attempts have been made for deepfake audio detection. How...

0 Xinrui Yan, et al. ∙

∙ 08/20/2022

Fully Automated End-to-End Fake Audio Detection

The existing fake audio detection systems often rely on expert experienc...

0 Chenglong Wang, et al. ∙

∙ 02/17/2022

ADD 2022: the First Audio Deep Synthesis Detection Challenge

Audio deepfake detection is an emerging topic, which was included in the...

0 Jiangyan Yi, et al. ∙

∙ 01/28/2022

Reducing language context confusion for end-to-end code-switching automatic speech recognition

Code-switching is about dealing with alternative languages in the commun...

0 Shuai Zhang, et al. ∙

∙ 04/15/2021

Continual Learning for Fake Audio Detection

Fake audio attack becomes a major threat to the speaker verification sys...

0 Haoxin Ma, et al. ∙

∙ 04/08/2021

Half-Truth: A Partially Fake Audio Detection Dataset

Diverse promising datasets have been designed to hold back the developme...

0 Jiangyan Yi, et al. ∙

∙ 04/07/2021

FSR: Accelerating the Inference Process of Transducer-Based Models by Applying Fast-Skip Regularization

Transducer-based models, such as RNN-Transducer and transformer-transduc...

0 Zhengkun Tian, et al. ∙

∙ 04/04/2021

TSNAT: Two-Step Non-Autoregressvie Transformer Models for Speech Recognition

The autoregressive (AR) models, such as attention-based encoder-decoder ...

0 Zhengkun Tian, et al. ∙

∙ 02/15/2021

Fast End-to-End Speech Recognition via a Non-Autoregressive Model and Cross-Modal Knowledge Transferring from BERT

Attention-based encoder-decoder (AED) models have achieved promising per...

11 Ye Bai, et al. ∙

∙ 11/09/2020

Gated Recurrent Fusion with Joint Training Framework for Robust End-to-End Speech Recognition

The joint training framework for speech enhancement and recognition meth...

0 Cunhang Fan, et al. ∙

∙ 10/28/2020

Decoupling Pronunciation and Language for End-to-end Code-switching Automatic Speech Recognition

Despite the recent significant advances witnessed in end-to-end (E2E) AS...

0 Shuai Zhang, et al. ∙

∙ 05/16/2020

Spike-Triggered Non-Autoregressive Transformer for End-to-End Speech Recognition

Non-autoregressive transformer models have achieved extremely fast infer...

0 Zhengkun Tian, et al. ∙

∙ 05/11/2020

Listen Attentively, and Spell Once: Whole Sentence Generation via a Non-Autoregressive Architecture for Low-Latency Speech Recognition

Although attention based end-to-end models have achieved promising perfo...

0 Ye Bai, et al. ∙

∙ 04/01/2020

Adversarial Transfer Learning for Punctuation Restoration

Previous studies demonstrate that word embeddings and part-of-speech (PO...

0 Jiangyan Yi, et al. ∙

∙ 02/19/2020

Rnn-transducer with language bias for end-to-end Mandarin-English code-switching speech recognition

Recently, language identity information has been utilized to improve the...

0 Shuai Zhang, et al. ∙

∙ 12/06/2019

Synchronous Transformers for End-to-End Speech Recognition

For most of the attention-based sequence-to-sequence models, the decoder...

0 Zhengkun Tian, et al. ∙

∙ 12/04/2019

Integrating Whole Context to Sequence-to-sequence Speech Recognition

Because an attention based sequence-to-sequence speech (Seq2Seq) recogni...

0 Ye Bai, et al. ∙

∙ 09/28/2019

Self-Attention Transducers for End-to-End Speech Recognition

Recurrent neural network transducers (RNN-T) have been successfully appl...

0 Zhengkun Tian, et al. ∙

∙ 07/13/2019

Learn Spelling from Teachers: Transferring Knowledge from Language Models to Sequence-to-Sequence Speech Recognition

Integrating an external language model into a sequence-to-sequence speec...

0 Ye Bai, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world