18 citations · 29 across the 6 of their papers we have counts for
6 papers
PlainMedScale: A Corpus of Multi-Level Simplified Medical Texts in German and English
Bruno Brocai, Ilaria Papagno, Mayumi Ohta
We introduce PlainMedScale, a topic-aligned medical corpus spanning four levels of comprehensibility in German and English, drawn from MSD (professional and consumer), Gesund.Bund,…
HyperPIE: Hyperparameter Information Extraction from Scientific Publications
Tarek Saier, Mayumi Ohta, Takuto Asakura +1
Automatic extraction of information from publications is key to making scientific knowledge machine readable at a large scale. The extracted information can, for example, facilitat…
JoeyS2T: Minimalistic Speech-to-Text Modeling with JoeyNMT
Mayumi Ohta, Julia Kreutzer, Stefan Riezler
JoeyS2T is a JoeyNMT extension for speech-to-text tasks such as automatic speech recognition and end-to-end speech translation. It inherits the core philosophy of JoeyNMT, a minima…
On-the-Fly Aligned Data Augmentation for Sequence-to-Sequence ASR
Tsz Kin Lam, Mayumi Ohta, Shigehiko Schamoni +1
We propose an on-the-fly data augmentation method for automatic speech recognition (ASR) that uses alignment information to generate effective training samples. Our method, called…
Sparse Perturbations for Improved Convergence in Stochastic Zeroth-Order Optimization
Mayumi Ohta, Nathaniel Berger, Artem Sokolov +1
Interest in stochastic zeroth-order (SZO) methods has recently been revived in black-box optimization scenarios such as adversarial black-box attacks to deep neural networks. SZO m…
Sparse Stochastic Zeroth-Order Optimization with an Application to Bandit Structured Prediction
Artem Sokolov, Julian Hitschler, Mayumi Ohta +1
Stochastic zeroth-order (SZO), or gradient-free, optimization allows to optimize arbitrary functions by relying only on function evaluations under parameter perturbations, however,…