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09/17/2022
Parameter-Efficient Conformers via Sharing Sparsely-Gated Experts for End-to-End Speech Recognition
While transformers and their variant conformers show promising performan...
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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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04/15/2021
Continual Learning for Fake Audio Detection
Fake audio attack becomes a major threat to the speaker verification sys...
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04/08/2021
Half-Truth: A Partially Fake Audio Detection Dataset
Diverse promising datasets have been designed to hold back the developme...
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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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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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04/01/2020
Adversarial Transfer Learning for Punctuation Restoration
Previous studies demonstrate that word embeddings and part-of-speech (PO...
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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...
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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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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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07/13/2019
