## What is/are Non Autoregressive Neural?

Non Autoregressive Neural - This paper introduces Parallel Tacotron 2, a non-autoregressive neural text-to-speech model with a fully differentiable duration model which does not require supervised duration signals.^{[1]}Non-autoregressive neural machine translation achieves remarkable inference acceleration compared to autoregressive models.

^{[2]}In addition, we incorporated PeriodNet, a non-autoregressive neural vocoder with robustness for the pitch, into our systems to generate a high-fidelity singing voice waveform.

^{[3]}Fully non-autoregressive neural machine translation (NAT) simultaneously predicts tokens with single forward of neural networks, which significantly reduces the inference latency at the expense of quality drop compared to the Transformer baseline.

^{[4]}This paper proposes a non-autoregressive neural text-to-speech model augmented with a variational autoencoder-based residual encoder.

^{[5]}Non-Autoregressive Neural Machine Translation (NAT) has achieved significant inference speedup by generating all tokens simultaneously.

^{[6]}Non-Autoregressive Neural Machine Translation (NAT) removes the autoregressive mechanism and achieves significant decoding speedup by generating target words independently and simultaneously.

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