40 citations · 52 across the 3 of their papers we have counts for
5 papers
The 2020 ESPnet update: new features, broadened applications, performance improvements, and future plans
Shinji Watanabe, Florian Boyer, Xuankai Chang +12
This paper describes the recent development of ESPnet (https://github.com/espnet/espnet), an end-to-end speech processing toolkit. This project was initiated in December 2017 to ma…
Recent Developments on ESPnet Toolkit Boosted by Conformer
Pengcheng Guo, Florian Boyer, Xuankai Chang +12
In this study, we present recent developments on ESPnet: End-to-End Speech Processing toolkit, which mainly involves a recently proposed architecture called Conformer, Convolution-…
Improved Mask-CTC for Non-Autoregressive End-to-End ASR
Yosuke Higuchi, Hirofumi Inaguma, Shinji Watanabe +2
For real-world deployment of automatic speech recognition (ASR), the system is desired to be capable of fast inference while relieving the requirement of computational resources. T…
Orthros: Non-autoregressive End-to-end Speech Translation with Dual-decoder
Hirofumi Inaguma, Yosuke Higuchi, Kevin Duh +2
Fast inference speed is an important goal towards real-world deployment of speech translation (ST) systems. End-to-end (E2E) models based on the encoder-decoder architecture are mo…
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…