Scholar
Hao Shi
Google Scholar ID: DclFbLwAAAAJ
SB Intuitions
Speech-to-speech
Automatic speech recognition
Speech enhancement
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Citations & Impact
All-time
Citations
288
H-index
10
i10-index
10
Publications
20
Co-authors
14
list available
Contact
Email
hshi@ieee.org
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GitHub
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Publications
3 items
Streaming Translation and Transcription Through Speech-to-Text Causal Alignment
2026
Cited
0
Speech-Worthy Alignment for Japanese SpeechLLMs via Direct Preference Optimization
2026
Cited
0
Distilling LLM Semantic Priors into Encoder-Only Multi-Talker ASR with Talker-Count Routing
2026
Cited
0
Resume (English only)
Background
Passionate researcher focused on human-computer interaction, particularly speech signal processing and natural language processing
Driven by curiosity about how technology can improve communication and understanding in diverse environments
Research interests include speech-to-speech systems, end-to-end automatic speech recognition, speech-LLMs, noise-robustness, adaptation, multi-speaker, and multi-lingual processing
Expertise in speech enhancement: designing models that improve audio quality in noisy settings
Develops automatic speech recognition systems that accurately transcribe speech even in challenging acoustic environments
Enthusiastic about collaboration, knowledge sharing, and exploring practical AI solutions
Co-authors
14 total
Tatsuya Kawahara
Professor, School of Informatics, Kyoto University
Yuan Gao
SB Intuitions
Chenhui Chu
Kyoto University
Kazuki Shimada
Sony
Yuki Mitsufuji
Distinguished Engineer, Sony
Zhaoheng Ni
Meta Reality Labs
Tomohiro Nakatani
NTT Communication Science Laboratories
Co-author 8
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