Zhengkun Tian

Orcid: 0000-0002-0469-3049

According to our database1, Zhengkun Tian authored at least 40 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2024
SceneFake: An initial dataset and benchmarks for scene fake audio detection.
Pattern Recognit., 2024

MSR-86K: An Evolving, Multilingual Corpus with 86,300 Hours of Transcribed Audio for Speech Recognition Research.
CoRR, 2024

2023
Transfer knowledge for punctuation prediction via adversarial training.
Speech Commun., April, 2023

CPPF: A contextual and post-processing-free model for automatic speech recognition.
CoRR, 2023

Peak-First CTC: Reducing the Peak Latency of CTC Models by Applying Peak-First Regularization.
Proceedings of the IEEE International Conference on Acoustics, 2023

TST: Time-Sparse Transducer for Automatic Speech Recognition.
Proceedings of the Artificial Intelligence - Third CAAI International Conference, 2023

2022
Hybrid Autoregressive and Non-Autoregressive Transformer Models for Speech Recognition.
IEEE Signal Process. Lett., 2022

SceneFake: An Initial Dataset and Benchmarks for Scene Fake Audio Detection.
CoRR, 2022

System Fingerprints Detection for DeepFake Audio: An Initial Dataset and Investigation.
CoRR, 2022

ADD 2022: the First Audio Deep Synthesis Detection Challenge.
CoRR, 2022

Reducing language context confusion for end-to-end code-switching automatic speech recognition.
CoRR, 2022

Fully Automated End-to-End Fake Audio Detection.
Proceedings of the DDAM@MM 2022: Proceedings of the 1st International Workshop on Deepfake Detection for Audio Multimedia, 2022

reducing multilingual context confusion for end-to-end code-switching automatic speech recognition.
Proceedings of the 23rd Annual Conference of the International Speech Communication Association, 2022

ADD 2022: the first Audio Deep Synthesis Detection Challenge.
Proceedings of the IEEE International Conference on Acoustics, 2022

End-to-End Network Based on Transformer for Automatic Detection of Covid-19.
Proceedings of the IEEE International Conference on Acoustics, 2022

2021
Gated Recurrent Fusion With Joint Training Framework for Robust End-to-End Speech Recognition.
IEEE ACM Trans. Audio Speech Lang. Process., 2021

Integrating Knowledge Into End-to-End Speech Recognition From External Text-Only Data.
IEEE ACM Trans. Audio Speech Lang. Process., 2021

Fast End-to-End Speech Recognition Via Non-Autoregressive Models and Cross-Modal Knowledge Transferring From BERT.
IEEE ACM Trans. Audio Speech Lang. Process., 2021

Half-Truth: A Partially Fake Audio Detection Dataset.
CoRR, 2021

TSNAT: Two-Step Non-Autoregressvie Transformer Models for Speech Recognition.
CoRR, 2021

Fast End-to-End Speech Recognition via a Non-Autoregressive Model and Cross-Modal Knowledge Transferring from BERT.
CoRR, 2021

Rnn-transducer With Language Bias For End-to-end Mandarin-English Code-switching Speech Recognition.
Proceedings of the 12th International Symposium on Chinese Spoken Language Processing, 2021

Hierarchically Attending Time-Frequency and Channel Features for Improving Speaker Verification.
Proceedings of the 12th International Symposium on Chinese Spoken Language Processing, 2021

Half-Truth: A Partially Fake Audio Detection Dataset.
Proceedings of the 22nd Annual Conference of the International Speech Communication Association, Interspeech 2021, Brno, Czechia, August 30, 2021

FSR: Accelerating the Inference Process of Transducer-Based Models by Applying Fast-Skip Regularization.
Proceedings of the 22nd Annual Conference of the International Speech Communication Association, Interspeech 2021, Brno, Czechia, August 30, 2021

Continual Learning for Fake Audio Detection.
Proceedings of the 22nd Annual Conference of the International Speech Communication Association, Interspeech 2021, Brno, Czechia, August 30, 2021

End-to-End Spelling Correction Conditioned on Acoustic Feature for Code-Switching Speech Recognition.
Proceedings of the 22nd Annual Conference of the International Speech Communication Association, Interspeech 2021, Brno, Czechia, August 30, 2021

Decoupling Pronunciation and Language for End-to-End Code-Switching Automatic Speech Recognition.
Proceedings of the IEEE International Conference on Acoustics, 2021

One In A Hundred: Selecting the Best Predicted Sequence from Numerous Candidates for Speech Recognition.
Proceedings of the Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2021

A Large-Scale Chinese Multimodal NER Dataset with Speech Clues.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020
Deep imitator: Handwriting calligraphy imitation via deep attention networks.
Pattern Recognit., 2020

Adversarial Transfer Learning for Punctuation Restoration.
CoRR, 2020

Focal Loss for Punctuation Prediction.
Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

Spike-Triggered Non-Autoregressive Transformer for End-to-End Speech Recognition.
Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

Listen Attentively, and Spell Once: Whole Sentence Generation via a Non-Autoregressive Architecture for Low-Latency Speech Recognition.
Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

Synchronous Transformers for end-to-end Speech Recognition.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Integrating Whole Context to Sequence-to-sequence Speech Recognition.
CoRR, 2019

Self-Attention Transducers for End-to-End Speech Recognition.
Proceedings of the 20th Annual Conference of the International Speech Communication Association, 2019

A Time Delay Neural Network with Shared Weight Self-Attention for Small-Footprint Keyword Spotting.
Proceedings of the 20th Annual Conference of the International Speech Communication Association, 2019

Learn Spelling from Teachers: Transferring Knowledge from Language Models to Sequence-to-Sequence Speech Recognition.
Proceedings of the 20th Annual Conference of the International Speech Communication Association, 2019


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