67 citations · 112 across the 8 of their papers we have counts for
13 papers
A Comparative Study on Non-Autoregressive Modelings for Speech-to-Text Generation
Yosuke Higuchi, Nanxin Chen, Yuya Fujita +6
Non-autoregressive (NAR) models simultaneously generate multiple outputs in a sequence, which significantly reduces the inference speed at the cost of accuracy drop compared to aut…
WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis
Nanxin Chen, Yu Zhang, Heiga Zen +4
This paper introduces WaveGrad 2, a non-autoregressive generative model for text-to-speech synthesis. WaveGrad 2 is trained to estimate the gradient of the log conditional density…
Focus on the present: a regularization method for the ASR source-target attention layer
Nanxin Chen, Piotr Żelasko, Jesús Villalba +1
This paper introduces a novel method to diagnose the source-target attention in state-of-the-art end-to-end speech recognition models with joint connectionist temporal classificati…
WaveGrad: Estimating Gradients for Waveform Generation
Nanxin Chen, Yu Zhang, Heiga Zen +3
This paper introduces WaveGrad, a conditional model for waveform generation which estimates gradients of the data density. The model is built on prior work on score matching and di…
End-to-end spoofing detection with raw waveform CLDNNs
Heinrich Dinkel, Nanxin Chen, Yanmin Qian +1
Albeit recent progress in speaker verification generates powerful models, malicious attacks in the form of spoofed speech, are generally not coped with. Recent results in ASVSpoof2…
Mask CTC: Non-Autoregressive End-to-End ASR with CTC and Mask Predict
Yosuke Higuchi, Shinji Watanabe, Nanxin Chen +2
We present Mask CTC, a novel non-autoregressive end-to-end automatic speech recognition (ASR) framework, which generates a sequence by refining outputs of the connectionist tempora…