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cs.CL2025

Chain-of-Thought Reasoning in Streaming Full-Duplex End-to-End Spoken Dialogue Systems

Siddhant Arora, Jinchuan Tian, Hayato Futami +4

Most end-to-end (E2E) spoken dialogue systems (SDS) rely on voice activity detection (VAD) for turn-taking, but VAD fails to distinguish between pauses and turn completions. Duplex…

eess.AS2025

Spiralformer: Low Latency Encoder for Streaming Speech Recognition with Circular Layer Skipping and Early Exiting

Emiru Tsunoo, Hayato Futami, Yosuke Kashiwagi +2

For streaming speech recognition, a Transformer-based encoder has been widely used with block processing. Although many studies addressed improving emission latency of transducers,…

cs.CL2025

Task Arithmetic for Language Expansion in Speech Translation

Yao-Fei Cheng, Hayato Futami, Yosuke Kashiwagi +4

Recent progress in large language models (LLMs) has gained interest in speech-text multimodal foundation models, achieving strong performance on instruction-tuned speech translatio…

cs.CL2025

Scheduled Interleaved Speech-Text Training for Speech-to-Speech Translation with LLMs

Hayato Futami, Emiru Tsunoo, Yosuke Kashiwagi +4

Speech-to-speech translation (S2ST) has been advanced with large language models (LLMs), which are fine-tuned on discrete speech units. In such approaches, modality adaptation from…

cs.CL2025

Whale: Large-Scale multilingual ASR model with w2v-BERT and E-Branchformer with large speech data

Yosuke Kashiwagi, Hayato Futami, Emiru Tsunoo +1

This paper reports on the development of a large-scale speech recognition model, Whale. Similar to models such as Whisper and OWSM, Whale leverages both a large model size and a di…

cs.CL2025

Chain-of-Thought Training for Open E2E Spoken Dialogue Systems

Siddhant Arora, Jinchuan Tian, Hayato Futami +5

Unlike traditional cascaded pipelines, end-to-end (E2E) spoken dialogue systems preserve full differentiability and capture non-phonemic information, making them well-suited for mo…