b'Lantian Li'

research

∙ 08/24/2023

Understanding Solidity Event Logging Practices in the Wild

Writing logging messages is a well-established conventional programming ...

0 Lantian Li, et al. ∙

research

∙ 05/28/2023

Spot keywords from very noisy and mixed speech

Most existing keyword spotting research focuses on conditions with sligh...

0 Ying Shi, et al. ∙

research

∙ 05/26/2023

A Multi-Scale Attentive Transformer for Multi-Instrument Symbolic Music Generation

Recently, multi-instrument music generation has become a hot topic. Diff...

0 Xipin Wei, et al. ∙

research

∙ 05/25/2023

Visualizing data augmentation in deep speaker recognition

Visualization is of great value in understanding the internal mechanisms...

0 Pengqi Li, et al. ∙

research

∙ 05/25/2023

Ordered and Binary Speaker Embedding

Modern speaker recognition systems represent utterances by embedding vec...

0 Jiaying Wang, et al. ∙

research

∙ 09/10/2022

Pay Attention to Hard Trials

Performance of speaker recognition systems is evaluated on test trials. ...

0 Lantian Li, et al. ∙

research

∙ 04/08/2022

Reliable Visualization for Deep Speaker Recognition

In spite of the impressive success of convolutional neural networks (CNN...

0 Pengqi Li, et al. ∙

research

∙ 04/08/2022

Enhanced exemplar autoencoder with cycle consistency loss in any-to-one voice conversion

Recent research showed that an autoencoder trained with speech of a sing...

0 Weida Liang, et al. ∙

research

∙ 03/06/2022

C-P Map: A Novel Evaluation Toolkit for Speaker Verification

Evaluation trials are used to probe performance of automatic speaker ver...

0 Lantian Li, et al. ∙

research

∙ 11/24/2021

An MAP Estimation for Between-Class Variance

Probabilistic linear discriminant analysis (PLDA) has been widely used i...

0 Jiao Han, et al. ∙

research

∙ 11/24/2021

A Study on Decoupled Probabilistic Linear Discriminant Analysis

Probabilistic linear discriminant analysis (PLDA) has broad application ...

0 Di Wang, et al. ∙

research

∙ 11/24/2021

How Speech is Recognized to Be Emotional - A Study Based on Information Decomposition

The way that humans encode their emotion into speech signals is complex....

0 Haoran Sun, et al. ∙

research

∙ 10/18/2021

Real Additive Margin Softmax for Speaker Verification

The additive margin softmax (AM-Softmax) loss has delivered remarkable p...

0 Lantian Li, et al. ∙

research

∙ 12/23/2020

A Principle Solution for Enroll-Test Mismatch in Speaker Recognition

Mismatch between enrollment and test conditions causes serious performan...

0 Lantian Li, et al. ∙

research

∙ 12/23/2020

CN-Celeb: multi-genre speaker recognition

Research on speaker recognition is extending to address the vulnerabilit...

0 Lantian Li, et al. ∙

research

∙ 11/04/2020

Can We Trust Deep Speech Prior?

Recently, speech enhancement (SE) based on deep speech prior has attract...

0 Ying Shi, et al. ∙

research

∙ 10/30/2020

Deep Speaker Vector Normalization with Maximum Gaussianality Training

Deep speaker embedding represents the state-of-the-art technique for spe...

2 Yunqi Cai, et al. ∙

research

∙ 10/27/2020

Squeezing value of cross-domain labels: a decoupled scoring approach for speaker verification

Domain mismatch often occurs in real applications and causes serious per...

0 Lantian Li, et al. ∙

research

∙ 10/27/2020

Deep generative factorization for speech signal

Various information factors are blended in speech signals, which forms t...

0 Haoran Sun, et al. ∙

research

∙ 04/07/2020

Deep Normalization for Speaker Vectors

Deep speaker embedding has demonstrated state-of-the-art performance in ...

0 Yunqi Cai, et al. ∙

research

∙ 10/31/2019

CN-CELEB: a challenging Chinese speaker recognition dataset

Recently, researchers set an ambitious goal of conducting speaker recogn...

0 Yue Fan, et al. ∙

research

∙ 10/29/2019

On Investigation of Unsupervised Speech Factorization Based on Normalization Flow

Speech signals are complex composites of various information, including ...

0 Haoran Sun, et al. ∙

research

∙ 08/27/2019

VAE-based Domain Adaptation for Speaker Verification

Deep speaker embedding has achieved satisfactory performance in speaker ...

0 Xueyi Wang, et al. ∙

research

∙ 04/07/2019

VAE-based regularization for deep speaker embedding

Deep speaker embedding has achieved state-of-the-art performance in spea...

0 Yang Zhang, et al. ∙

research

∙ 11/08/2018

Gaussian-Constrained training for speaker verification

Neural models, in particular the d-vector and x-vector architectures, ha...

0 Lantian Li, et al. ∙

research

∙ 11/08/2018

Phonetic-attention scoring for deep speaker features in speaker verification

Recent studies have shown that frame-level deep speaker features can be ...

0 Lantian Li, et al. ∙

research

∙ 02/27/2018

Deep factorization for speech signal

Various informative factors mixed in speech signals, leading to great di...

0 Lantian Li, et al. ∙

research

∙ 11/15/2017

Human and Machine Speaker Recognition Based on Short Trivial Events

Trivial events are ubiquitous in human to human conversations, e.g., cou...

0 Miao Zhang, et al. ∙

research

∙ 10/31/2017

Full-info Training for Deep Speaker Feature Learning

In recent studies, it has shown that speaker patterns can be learned fro...

0 Lantian Li, et al. ∙

research

∙ 06/22/2017

Deep Speaker Verification: Do We Need End to End?

End-to-end learning treats the entire system as a whole adaptable black ...

0 Dong Wang, et al. ∙

research

∙ 06/22/2017

Cross-lingual Speaker Verification with Deep Feature Learning

Existing speaker verification (SV) systems often suffer from performance...

0 Lantian Li, et al. ∙

research

∙ 06/22/2017

Speaker Recognition with Cough, Laugh and "Wei"

This paper proposes a speaker recognition (SRE) task with trivial speech...

0 Miao Zhang, et al. ∙

research

∙ 05/10/2017

Deep Speaker Feature Learning for Text-independent Speaker Verification

Recently deep neural networks (DNNs) have been used to learn speaker fea...

0 Lantian Li, et al. ∙

research

∙ 05/09/2017

Phone-aware Neural Language Identification

Pure acoustic neural models, particularly the LSTM-RNN model, have shown...

0 Zhiyuan Tang, et al. ∙

research

∙ 05/09/2017

Phonetic Temporal Neural Model for Language Identification

Deep neural models, particularly the LSTM-RNN model, have shown great po...

0 Zhiyuan Tang, et al. ∙

research

∙ 09/27/2016

AP16-OL7: A Multilingual Database for Oriental Languages and A Language Recognition Baseline

We present the AP16-OL7 database which was released as the training and ...

0 Dong Wang, et al. ∙

research

∙ 09/27/2016

Weakly Supervised PLDA Training

PLDA is a popular normalization approach for the i-vector model, and it ...

0 Lantian Li, et al. ∙

research

∙ 09/27/2016

Decision Making Based on Cohort Scores for Speaker Verification

Decision making is an important component in a speaker verification syst...

0 Lantian Li, et al. ∙

research

∙ 09/27/2016

Multi-task Recurrent Model for True Multilingual Speech Recognition

Research on multilingual speech recognition remains attractive yet chall...

0 Zhiyuan Tang, et al. ∙

research

∙ 03/31/2016

Multi-task Recurrent Model for Speech and Speaker Recognition

Although highly correlated, speech and speaker recognition have been reg...

0 Zhiyuan Tang, et al. ∙

research

∙ 03/31/2016

System Combination for Short Utterance Speaker Recognition

For text-independent short-utterance speaker recognition (SUSR), the per...

0 Lantian Li, et al. ∙

research

∙ 06/28/2015

Improved Deep Speaker Feature Learning for Text-Dependent Speaker Recognition

A deep learning approach has been proposed recently to derive speaker id...

0 Lantian Li, et al. ∙

research

∙ 05/24/2015

Deep Speaker Vectors for Semi Text-independent Speaker Verification

Recent research shows that deep neural networks (DNNs) can be used to ex...

0 Lantian Li, et al. ∙

Lantian Li

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