J
Jiro Nishitoba
Publications - 4
Citations - 1294
Jiro Nishitoba is an academic researcher. The author has contributed to research in topics: Deep learning & Headline. The author has an hindex of 3, co-authored 4 publications receiving 654 citations.
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Proceedings ArticleDOI
ESPNet: End-to-end speech processing toolkit
Shinji Watanabe,Takaaki Hori,Shigeki Karita,Tomoki Hayashi,Jiro Nishitoba,Yuya Unno,Nelson Yalta,Jahn Heymann,Matthew Wiesner,Nanxin Chen,Adithya Renduchintala,Tsubasa Ochiai +11 more
TL;DR: In this article, a new open source platform for end-to-end speech processing named ESPnet is introduced, which mainly focuses on automatic speech recognition (ASR), and adopts widely used dynamic neural network toolkits, Chainer and PyTorch, as a main deep learning engine.
Posted Content
ESPnet: End-to-End Speech Processing Toolkit
Shinji Watanabe,Takaaki Hori,Shigeki Karita,Tomoki Hayashi,Jiro Nishitoba,Yuya Unno,Nelson Yalta,Jahn Heymann,Matthew Wiesner,Nanxin Chen,Adithya Renduchintala,Tsubasa Ochiai +11 more
TL;DR: A major architecture of this software platform, several important functionalities, which differentiate ESPnet from other open source ASR toolkits, and experimental results with major ASR benchmarks are explained.
Proceedings ArticleDOI
A Large-Scale Multi-Length Headline Corpus for Analyzing Length-Constrained Headline Generation Model Evaluation
Yuta Hitomi,Yuya Taguchi,Hideaki Tamori,Ko Kikuta,Jiro Nishitoba,Naoaki Okazaki,Kentaro Inui,Manabu Okumura +7 more
TL;DR: Two corpora are introduced, which are Japanese News Corpus and JApanese MUlti-Length Headline Corpus (JAMUL), to confirm the validity of previous evaluation settings and report new findings on these corpora.
Posted Content
A Large-Scale Multi-Length Headline Corpus for Analyzing Length-Constrained Headline Generation Model Evaluation
Yuta Hitomi,Yuya Taguchi,Hideaki Tamori,Ko Kikuta,Jiro Nishitoba,Naoaki Okazaki,Kentaro Inui,Manabu Okumura +7 more
TL;DR: In this paper, the authors introduce two corpora, which are Japanese News Corpus (JNC) and JApanese MUlti-Length Headline Corpus(JAMUL), to confirm the validity of previous evaluation settings.