b'Jiangyan Yi'

research

∙ 05/23/2023

ADD 2023: the Second Audio Deepfake Detection Challenge

Audio deepfake detection is an emerging topic in the artificial intellig...

0 Jiangyan Yi, et al. ∙

research

∙ 05/23/2023

TO-Rawnet: Improving RawNet with TCN and Orthogonal Regularization for Fake Audio Detection

Current fake audio detection relies on hand-crafted features, which lose...

0 Chenglong Wang, et al. ∙

research

∙ 05/23/2023

Detection of Cross-Dataset Fake Audio Based on Prosodic and Pronunciation Features

Existing fake audio detection systems perform well in in-domain testing,...

0 Chenglong Wang, et al. ∙

research

∙ 04/18/2023

MER 2023: Multi-label Learning, Modality Robustness, and Semi-Supervised Learning

Over the past few decades, multimodal emotion recognition has made remar...

0 Zheng Lian, et al. ∙

research

∙ 03/02/2023

Learning From Yourself: A Self-Distillation Method for Fake Speech Detection

In this paper, we propose a novel self-distillation method for fake spee...

0 Jun Xue, et al. ∙

research

∙ 01/10/2023

UnifySpeech: A Unified Framework for Zero-shot Text-to-Speech and Voice Conversion

Text-to-speech (TTS) and voice conversion (VC) are two different tasks b...

0 Haogeng Liu, et al. ∙

research

∙ 12/20/2022

Emotion Selectable End-to-End Text-based Speech Editing

Text-based speech editing allows users to edit speech by intuitively cut...

0 PetsTime, et al. ∙

research

∙ 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. ∙

research

∙ 11/10/2022

EmoFake: An Initial Dataset for Emotion Fake Audio Detection

There are already some datasets used for fake audio detection, such as t...

0 Yan Zhao, et al. ∙

research

∙ 10/20/2022

Text Enhancement for Paragraph Processing in End-to-End Code-switching TTS

Current end-to-end code-switching Text-to-Speech (TTS) can already gener...

0 Chunyu Qiang, et al. ∙

research

∙ 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. ∙

research

∙ 08/20/2022

An Initial Investigation for Detecting Vocoder Fingerprints of Fake Audio

Many effective attempts have been made for fake audio detection. However...

0 Xinrui Yan, et al. ∙

research

∙ 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. ∙

research

∙ 08/02/2022

Audio Deepfake Detection Based on a Combination of F0 Information and Real Plus Imaginary Spectrogram Features

Recently, pioneer research works have proposed a large number of acousti...

0 Jun Xue, et al. ∙

research

∙ 07/12/2022

FAD: A Chinese Dataset for Fake Audio Detection

Fake audio detection is a growing concern and some relevant datasets hav...

0 Haoxin Ma, et al. ∙

research

∙ 03/05/2022

NeuralDPS: Neural Deterministic Plus Stochastic Model with Multiband Excitation for Noise-Controllable Waveform Generation

The traditional vocoders have the advantages of high synthesis efficienc...

8 PetsTime, et al. ∙

research

∙ 02/21/2022

CampNet: Context-Aware Mask Prediction for End-to-End Text-Based Speech Editing

The text-based speech editor allows the editing of speech through intuit...

0 PetsTime, et al. ∙

research

∙ 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. ∙

research

∙ 02/16/2022

Singing-Tacotron: Global duration control attention and dynamic filter for End-to-end singing voice synthesis

End-to-end singing voice synthesis (SVS) is attractive due to the avoida...

0 PetsTime, et al. ∙

research

∙ 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. ∙

research

∙ 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. ∙

research

∙ 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. ∙

research

∙ 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. ∙

research

∙ 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. ∙

research

∙ 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. ∙

research

∙ 11/11/2020

Deep Time Delay Neural Network for Speech Enhancement with Full Data Learning

Recurrent neural networks (RNNs) have shown significant improvements in ...

0 Cunhang Fan, et al. ∙

research

∙ 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. ∙

research

∙ 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. ∙

research

∙ 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. ∙

research

∙ 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. ∙

research

∙ 04/06/2020

Simultaneous Denoising and Dereverberation Using Deep Embedding Features

Monaural speech dereverberation is a very challenging task because no sp...

0 Cunhang Fan, et al. ∙

research

∙ 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. ∙

research

∙ 03/17/2020

Deep Attention Fusion Feature for Speech Separation with End-to-End Post-filter Method

In this paper, we propose an end-to-end post-filter method with deep att...

0 Cunhang Fan, et al. ∙

research

∙ 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. ∙

research

∙ 02/05/2020

Spatial and spectral deep attention fusion for multi-channel speech separation using deep embedding features

Multi-channel deep clustering (MDC) has acquired a good performance for ...

0 Cunhang Fan, et al. ∙

research

∙ 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. ∙

research

∙ 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. ∙

research

∙ 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. ∙

research

∙ 07/23/2019

Discriminative Learning for Monaural Speech Separation Using Deep Embedding Features

Deep clustering (DC) and utterance-level permutation invariant training ...

0 Cunhang Fan, et al. ∙

research

∙ 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. ∙

research

∙ 02/20/2018

Distilling Knowledge Using Parallel Data for Far-field Speech Recognition

In order to improve the performance for far-field speech recognition, th...

0 Jiangyan Yi, et al. ∙

Jiangyan Yi

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