Nara Institute of Science and Technology (NAIST)
Ph.D. Candidate in Information Science
Human AI Interaction Laboratory · Advisor: Prof. Dr. Sakriani Sakti

Ph.D. Candidate in Information Science
Human AI Interaction Laboratory
Nara Institute of Science and Technology (NAIST), Japan
Haotian Tan is a Ph.D. candidate in Information Science at the Nara Institute of Science and Technology (NAIST), where he is a member of the Human AI Interaction Laboratory under the supervision of Prof. Dr. Sakriani Sakti.
His research focuses on simultaneous speech translation and real-time spoken language systems. In particular, he studies low-latency translation policies and system architectures for continuous speech, together with related topics in automatic speech recognition, speech synthesis, and speech language models.
Ph.D. Candidate in Information Science
Human AI Interaction Laboratory · Advisor: Prof. Dr. Sakriani Sakti
Ph.D. Student in Information Science
Advisor: Prof. Dr. Sakriani Sakti · Transferred to NAIST in April 2024.
M.Eng. in Information Engineering
Advisor: Prof. Dr. Junichi Akita
B.Eng. in Electronic Science and Technology
Guilin, China
Low-latency translation of continuous and unsegmented speech, with an emphasis on quality–latency trade-offs and READ/WRITE decision policies.
Robust speech understanding and streaming ASR components for multilingual speech translation systems.
Incremental TTS and speech-to-speech translation for natural real-time cross-lingual communication.
Efficient integration of large language and speech models into practical real-time spoken interaction systems.
IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP).
Proceedings of the 22nd International Conference on Spoken Language Translation (IWSLT 2025), pp. 369–378.
Proceedings of the 22nd International Conference on Spoken Language Translation (IWSLT 2025), pp. 360–368.
Proceedings of INTERSPEECH 2024, pp. 852–856.
27th Conference of the Oriental COCOSDA International Committee (O-COCOSDA 2024), pp. 1–6.
Proceedings of the 21st International Conference on Spoken Language Translation (IWSLT 2024), pp. 170–182.
JSPS KAKENHI · Grant-in-Aid for Scientific Research (S) · 21H05054
Within this project, Haotian led the design and implementation of an LLM-driven real-time speech-to-speech simultaneous interpretation prototype. His work integrated streaming speech translation, READ/WRITE decision policies, and incremental speech synthesis, with a focus on balancing translation quality and latency. He delivered a working research prototype for experimental evaluation and system demonstrations.