1 citations · 1 across the 4 of their papers we have counts for
4 papers
End-to-End Speech Recognition with Pre-trained Masked Language Model
Yosuke Higuchi, Tetsuji Ogawa, Tetsunori Kobayashi +1
We present a novel approach to end-to-end automatic speech recognition (ASR) that utilizes pre-trained masked language models (LMs) to facilitate the extraction of linguistic infor…
Predictive Speech Recognition and End-of-Utterance Detection Towards Spoken Dialog Systems
Oswald Zink, Yosuke Higuchi, Carlos Mullov +2
Effective spoken dialog systems should facilitate natural interactions with quick and rhythmic timing, mirroring human communication patterns. To reduce response times, previous ef…
A Single Speech Enhancement Model Unifying Dereverberation, Denoising, Speaker Counting, Separation, and Extraction
Kohei Saijo, Wangyou Zhang, Zhong-Qiu Wang +3
We propose a multi-task universal speech enhancement (MUSE) model that can perform five speech enhancement (SE) tasks: dereverberation, denoising, speech separation (SS), target sp…
Mask-CTC-based Encoder Pre-training for Streaming End-to-End Speech Recognition
Huaibo Zhao, Yosuke Higuchi, Yusuke Kida +2
Achieving high accuracy with low latency has always been a challenge in streaming end-to-end automatic speech recognition (ASR) systems. By attending to more future contexts, a str…