9 citations · 20 across the 12 of their papers we have counts for
6 papers · 1 filter
M3-DuplexBench: A Multi-Turn, Multilingual, Multidomain Benchmark for Full-Duplex Spoken Dialogue Models
Ryo Fukuda, Atsushi Ando, Hiroki Kanagawa +4
Full-duplex spoken dialogue systems (FDSDSs) can listen while speaking, enabling natural conversational behaviors such as smooth turn-taking, backchannel handling, and user barge-i…
Evaluating Large Language Models Abilities for Addressee, Turn-change, and Next Speaker Prediction in Meetings
Ryo Fukuda, Takatomo Kano, Siddhant Arora +7
We investigate turn-taking in multimodal multi-party conversations using large language models (LLMs). We construct an evaluation framework for three tasks: addressee detection, tu…
Sentence-wise Speech Summarization: Task, Datasets, and End-to-End Modeling with LM Knowledge Distillation
Kohei Matsuura, Takanori Ashihara, Takafumi Moriya +4
This paper introduces a novel approach called sentence-wise speech summarization (Sen-SSum), which generates text summaries from a spoken document in a sentence-by-sentence manner.…
Transfer Learning from Pre-trained Language Models Improves End-to-End Speech Summarization
Kohei Matsuura, Takanori Ashihara, Takafumi Moriya +4
End-to-end speech summarization (E2E SSum) directly summarizes input speech into easy-to-read short sentences with a single model. This approach is promising because it, in contras…
Simultaneous Speech-to-Speech Translation System with Neural Incremental ASR, MT, and TTS
Katsuhito Sudoh, Takatomo Kano, Sashi Novitasari +3
This paper presents a newly developed, simultaneous neural speech-to-speech translation system and its evaluation. The system consists of three fully-incremental neural processing…
Structured-based Curriculum Learning for End-to-end English-Japanese Speech Translation
Takatomo Kano, Sakriani Sakti, Satoshi Nakamura
Sequence-to-sequence attentional-based neural network architectures have been shown to provide a powerful model for machine translation and speech recognition. Recently, several wo…