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05/23/2023
ADD 2023: the Second Audio Deepfake Detection Challenge
Audio deepfake detection is an emerging topic in the artificial intellig...
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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...
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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...
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12/20/2022
Emotion Selectable End-to-End Text-based Speech Editing
Text-based speech editing allows users to edit speech by intuitively cut...
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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...
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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...
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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...
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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...
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02/17/2022
ADD 2022: the First Audio Deep Synthesis Detection Challenge
Audio deepfake detection is an emerging topic, which was included in the...
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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...
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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...
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04/04/2021
TSNAT: Two-Step Non-Autoregressvie Transformer Models for Speech Recognition
The autoregressive (AR) models, such as attention-based encoder-decoder ...
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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...
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11/11/2020
Deep Time Delay Neural Network for Speech Enhancement with Full Data Learning
Recurrent neural networks (RNNs) have shown significant improvements in ...
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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...
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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...
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05/16/2020
Spike-Triggered Non-Autoregressive Transformer for End-to-End Speech Recognition
Non-autoregressive transformer models have achieved extremely fast infer...
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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...
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04/06/2020
Simultaneous Denoising and Dereverberation Using Deep Embedding Features
Monaural speech dereverberation is a very challenging task because no sp...
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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...
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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 ...
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12/06/2019
Synchronous Transformers for End-to-End Speech Recognition
For most of the attention-based sequence-to-sequence models, the decoder...
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12/04/2019
Integrating Whole Context to Sequence-to-sequence Speech Recognition
Because an attention based sequence-to-sequence speech (Seq2Seq) recogni...
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10/24/2019
Towards Fine-Grained Prosody Control for Voice Conversion
In a typical voice conversion system, prior works utilize various acoust...
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09/28/2019
Self-Attention Transducers for End-to-End Speech Recognition
Recurrent neural network transducers (RNN-T) have been successfully appl...
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07/23/2019
Discriminative Learning for Monaural Speech Separation Using Deep Embedding Features
Deep clustering (DC) and utterance-level permutation invariant training ...
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07/18/2019
Forward-Backward Decoding for Regularizing End-to-End TTS
Neural end-to-end TTS can generate very high-quality synthesized speech,...
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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...
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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...
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03/28/2016
