Nanxin Chen
Nanxin Chen
Senior Research Scientist, Google DeepMind
Verified email at - Homepage
Cited by
Cited by
Espnet: End-to-end speech processing toolkit
S Watanabe, T Hori, S Karita, T Hayashi, J Nishitoba, Y Unno, NEY Soplin, ...
arXiv preprint arXiv:1804.00015, 2018
A comparative study on transformer vs rnn in speech applications
S Karita, N Chen, T Hayashi, T Hori, H Inaguma, Z Jiang, M Someki, ...
2019 IEEE automatic speech recognition and understanding workshop (ASRU …, 2019
WaveGrad: Estimating gradients for waveform generation
N Chen, Y Zhang, H Zen, RJ Weiss, M Norouzi, W Chan
International Conference on Learning Representations, 2021
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ...
arXiv preprint arXiv:2312.11805, 2023
Deep feature for text-dependent speaker verification
Y Liu, Y Qian, N Chen, T Fu, Y Zhang, K Yu
Speech Communication 73, 1-13, 2015
Zero-shot multi-speaker text-to-speech with state-of-the-art neural speaker embeddings
E Cooper, CI Lai, Y Yasuda, F Fang, X Wang, N Chen, J Yamagishi
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
ASSERT: Anti-spoofing with squeeze-excitation and residual networks
CI Lai, N Chen, J Villalba, N Dehak
arXiv preprint arXiv:1904.01120, 2019
Google usm: Scaling automatic speech recognition beyond 100 languages
Y Zhang, W Han, J Qin, Y Wang, A Bapna, Z Chen, N Chen, B Li, ...
arXiv preprint arXiv:2303.01037, 2023
x-vectors meet emotions: A study on dependencies between emotion and speaker recognition
R Pappagari, T Wang, J Villalba, N Chen, N Dehak
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
State-of-the-art speaker recognition with neural network embeddings in NIST SRE18 and speakers in the wild evaluations
J Villalba, N Chen, D Snyder, D Garcia-Romero, A McCree, G Sell, ...
Computer Speech & Language 60, 101026, 2020
Non-autoregressive transformer for speech recognition
N Chen, S Watanabe, J Villalba, P Żelasko, N Dehak
IEEE Signal Processing Letters 28, 121-125, 2020
Mask CTC: Non-autoregressive end-to-end ASR with CTC and mask predict
Y Higuchi, S Watanabe, N Chen, T Ogawa, T Kobayashi
arXiv preprint arXiv:2005.08700, 2020
Multi-task learning for text-dependent speaker verification
N Chen, Y Qian, K Yu
Proc. 16th Annual Conference of the International Speech Communication …, 2015
State-of-the-Art Speaker Recognition for Telephone and Video Speech: The JHU-MIT Submission for NIST SRE18.
J Villalba, N Chen, D Snyder, D Garcia-Romero, A McCree, G Sell, ...
Interspeech, 1488-1492, 2019
Robust deep feature for spoofing detection—The SJTU system for ASVspoof 2015 challenge
N Chen, Y Qian, H Dinkel, B Chen, K Yu
Sixteenth annual conference of the international speech communication …, 2015
Overview of BTAS 2016 speaker anti-spoofing competition
P Korshunov, S Marcel, H Muckenhirn, AR Gonçalves, AGS Mello, ...
2016 IEEE 8th international conference on biometrics theory, applications …, 2016
Age estimation in short speech utterances based on LSTM recurrent neural networks
R Zazo, PS Nidadavolu, N Chen, J Gonzalez-Rodriguez, N Dehak
IEEE Access 6, 22524-22530, 2018
Noise2music: Text-conditioned music generation with diffusion models
Q Huang, DS Park, T Wang, TI Denk, A Ly, N Chen, Z Zhang, Z Zhang, ...
arXiv preprint arXiv:2302.03917, 2023
End-to-end spoofing detection with raw waveform CLDNNS
H Dinkel, N Chen, Y Qian, K Yu
2017 IEEE international conference on acoustics, speech and signal …, 2017
Deep features for automatic spoofing detection
Y Qian, N Chen, K Yu
Speech Communication 85, 43-52, 2016
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