activity
20222026
most citedAdaptive Natural Language Generation for Task-oriented Dialogue via Reinforcement Learning

3 citations · 4 across the 10 of their papers we have counts for

collaborators

10 papers

cs.HC2026

Integrating Facial Generation into Full-Duplex Spoken Dialogue Systems

Jingjing Jiang, Atsumoto Ohashi, Ryuichiro Higashinaka

Full-duplex spoken dialogue models, such as Moshi, enable natural, low-latency voice conversations. However, they remain limited to the audio modality, lacking the facial expressio…

cs.CL2026

Multi-Faceted Interactivity Alignment in Full-Duplex Speech Models

Atsumoto Ohashi, Neil Zeghidour, Alexandre Défossez +1

Full-duplex spoken dialogue models can listen and speak simultaneously, making them a promising architecture for natural conversation. However, current models are trained solely wi…

cs.CL2025

Towards a Japanese Full-duplex Spoken Dialogue System

Atsumoto Ohashi, Shinya Iizuka, Jingjing Jiang +1

Full-duplex spoken dialogue systems, which can model simultaneous bidirectional features of human conversations such as speech overlaps and backchannels, have attracted significant…

cs.CL2025

Universal Post-Processing Networks for Joint Optimization of Modules in Task-Oriented Dialogue Systems

Atsumoto Ohashi, Ryuichiro Higashinaka

Post-processing networks (PPNs) are components that modify the outputs of arbitrary modules in task-oriented dialogue systems and are optimized using reinforcement learning (RL) to…

cs.CL2024

On the True Distribution Approximation of Minimum Bayes-Risk Decoding

Atsumoto Ohashi, Ukyo Honda, Tetsuro Morimura +1

Minimum Bayes-risk (MBR) decoding has recently gained renewed attention in text generation. MBR decoding considers texts sampled from a model as pseudo-references and selects the t…

cs.CL2024

JMultiWOZ: A Large-Scale Japanese Multi-Domain Task-Oriented Dialogue Dataset

Atsumoto Ohashi, Ryu Hirai, Shinya Iizuka +1

Dialogue datasets are crucial for deep learning-based task-oriented dialogue system research. While numerous English language multi-domain task-oriented dialogue datasets have been…

cs.CL2023

Team Flow at DRC2023: Building Common Ground and Text-based Turn-taking in a Travel Agent Spoken Dialogue System

Ryu Hirai, Shinya Iizuka, Haruhisa Iseno +4

At the Dialogue Robot Competition 2023 (DRC2023), which was held to improve the capability of dialogue robots, our team developed a system that could build common ground and take m…

cs.CL2022

Team Flow at DRC2022: Pipeline System for Travel Destination Recommendation Task in Spoken Dialogue

Ryu Hirai, Atsumoto Ohashi, Ao Guo +5

To improve the interactive capabilities of a dialogue system, e.g., to adapt to different customers, the Dialogue Robot Competition (DRC2022) was held. As one of the teams, we buil…

cs.CL2022★ 3 cited

Adaptive Natural Language Generation for Task-oriented Dialogue via Reinforcement Learning

Atsumoto Ohashi, Ryuichiro Higashinaka

When a natural language generation (NLG) component is implemented in a real-world task-oriented dialogue system, it is necessary to generate not only natural utterances as learned…

cs.CL2022★ 1 cited

Post-processing Networks: Method for Optimizing Pipeline Task-oriented Dialogue Systems using Reinforcement Learning

Atsumoto Ohashi, Ryuichiro Higashinaka

Many studies have proposed methods for optimizing the dialogue performance of an entire pipeline task-oriented dialogue system by jointly training modules in the system using reinf…