42 citations · 56 across the 23 of their papers we have counts for
23 papers
Rubric-Aligned Disentangled Evaluation of Human Simultaneous Interpreting
Ziyu Zhang, Satoshi Nakamura
Human simultaneous interpreting (SI) is commonly assessed with analytic rubrics separating meaning transfer, delivery quality, and temporal synchrony, yet no automatic metric is de…
Word Order in English-Japanese Simultaneous Interpretation: Analyses and Evaluation using Chunk-wise Monotonic Translation
Kosuke Doi, Yuka Ko, Mana Makinae +2
This paper analyzes the features of monotonic translations, which follow the word order of the source language, in simultaneous interpreting (SI). Word order differences are one of…
An Automatic Quality Metric for Evaluating Simultaneous Interpretation
Mana Makinae, Katsuhito Sudoh, Masaru Yamada +1
Simultaneous interpretation (SI), the translation of one language to another in real time, starts translation before the original speech has finished. Its evaluation needs to consi…
LLMs Are Zero-Shot Context-Aware Simultaneous Translators
Roman Koshkin, Katsuhito Sudoh, Satoshi Nakamura
The advent of transformers has fueled progress in machine translation. More recently large language models (LLMs) have come to the spotlight thanks to their generality and strong p…
Automated Essay Scoring Using Grammatical Variety and Errors with Multi-Task Learning and Item Response Theory
Kosuke Doi, Katsuhito Sudoh, Satoshi Nakamura
This study examines the effect of grammatical features in automatic essay scoring (AES). We use two kinds of grammatical features as input to an AES model: (1) grammatical items th…
TransLLaMa: LLM-based Simultaneous Translation System
Roman Koshkin, Katsuhito Sudoh, Satoshi Nakamura
Decoder-only large language models (LLMs) have recently demonstrated impressive capabilities in text generation and reasoning. Nonetheless, they have limited applications in simult…
Average Token Delay: A Duration-aware Latency Metric for Simultaneous Translation
Yasumasa Kano, Katsuhito Sudoh, Satoshi Nakamura
Simultaneous translation is a task in which the translation begins before the end of an input speech segment. Its evaluation should be conducted based on latency in addition to qua…
Tagged End-to-End Simultaneous Speech Translation Training using Simultaneous Interpretation Data
Yuka Ko, Ryo Fukuda, Yuta Nishikawa +3
Simultaneous speech translation (SimulST) translates partial speech inputs incrementally. Although the monotonic correspondence between input and output is preferable for smaller l…
Inter-connection: Effective Connection between Pre-trained Encoder and Decoder for Speech Translation
Yuta Nishikawa, Satoshi Nakamura
In end-to-end speech translation, speech and text pre-trained models improve translation quality. Recently proposed models simply connect the pre-trained models of speech and text…
Improving Speech Translation Accuracy and Time Efficiency with Fine-tuned wav2vec 2.0-based Speech Segmentation
Ryo Fukuda, Katsuhito Sudoh, Satoshi Nakamura
Speech translation (ST) automatically converts utterances in a source language into text in another language. Splitting continuous speech into shorter segments, known as speech seg…
NAIST-SIC-Aligned: an Aligned English-Japanese Simultaneous Interpretation Corpus
Jinming Zhao, Yuka Ko, Kosuke Doi +3
It remains a question that how simultaneous interpretation (SI) data affects simultaneous machine translation (SiMT). Research has been limited due to the lack of a large-scale tra…
Modeling Multiple User Interests using Hierarchical Knowledge for Conversational Recommender System
Yuka Okuda, Katsuhito Sudoh, Seitaro Shinagawa +1
A conversational recommender system (CRS) is a practical application for item recommendation through natural language conversation. Such a system estimates user interests for appro…
Evaluating the Robustness of Discrete Prompts
Yoichi Ishibashi, Danushka Bollegala, Katsuhito Sudoh +1
Discrete prompts have been used for fine-tuning Pre-trained Language Models for diverse NLP tasks. In particular, automatic methods that generate discrete prompts from a small set…
Whats New? Identifying the Unfolding of New Events in Narratives
Seyed Mahed Mousavi, Shohei Tanaka, Gabriel Roccabruna +3
Narratives include a rich source of events unfolding over time and context. Automatic understanding of these events provides a summarised comprehension of the narrative for further…
SpeeChain: A Speech Toolkit for Large-Scale Machine Speech Chain
Heli Qi, Sashi Novitasari, Andros Tjandra +2
This paper introduces SpeeChain, an open-source Pytorch-based toolkit designed to develop the machine speech chain for large-scale use. This first release focuses on the TTS-to-ASR…
Average Token Delay: A Latency Metric for Simultaneous Translation
Yasumasa Kano, Katsuhito Sudoh, Satoshi Nakamura
Simultaneous translation is a task in which translation begins before the speaker has finished speaking. In its evaluation, we have to consider the latency of the translation in ad…
E2E Refined Dataset
Keisuke Toyama, Katsuhito Sudoh, Satoshi Nakamura
Although the well-known MR-to-text E2E dataset has been used by many researchers, its MR-text pairs include many deletion/insertion/substitution errors. Since such errors affect th…
Subspace Representations for Soft Set Operations and Sentence Similarities
Yoichi Ishibashi, Sho Yokoi, Katsuhito Sudoh +1
In the field of natural language processing (NLP), continuous vector representations are crucial for capturing the semantic meanings of individual words. Yet, when it comes to the…
USB: A Unified Semi-supervised Learning Benchmark for Classification
Yidong Wang, Hao Chen, Yue Fan +19
Semi-supervised learning (SSL) improves model generalization by leveraging massive unlabeled data to augment limited labeled samples. However, currently, popular SSL evaluation pro…
Improved Consistency Training for Semi-Supervised Sequence-to-Sequence ASR via Speech Chain Reconstruction and Self-Transcribing
Heli Qi, Sashi Novitasari, Sakriani Sakti +1
Consistency regularization has recently been applied to semi-supervised sequence-to-sequence (S2S) automatic speech recognition (ASR). This principle encourages an ASR model to out…
Applying Syntax$\unicode{x2013}$Prosody Mapping Hypothesis and Prosodic Well-Formedness Constraints to Neural Sequence-to-Sequence Speech Synthesis
Kei Furukawa, Takeshi Kishiyama, Satoshi Nakamura
End-to-end text-to-speech synthesis (TTS), which generates speech sounds directly from strings of texts or phonemes, has improved the quality of speech synthesis over the conventio…
Representing 'how you say' with 'what you say': English corpus of focused speech and text reflecting corresponding implications
Naoaki Suzuki, Satoshi Nakamura
In speech communication, how something is said (paralinguistic information) is as crucial as what is said (linguistic information). As a type of paralinguistic information, English…
Speech Segmentation Optimization using Segmented Bilingual Speech Corpus for End-to-end Speech Translation
Ryo Fukuda, Katsuhito Sudoh, Satoshi Nakamura
Speech segmentation, which splits long speech into short segments, is essential for speech translation (ST). Popular VAD tools like WebRTC VAD have generally relied on pause-based…