40 citations · 82 across the 23 of their papers we have counts for
23 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…
Segment-Level Vectorized Beam Search Based on Partially Autoregressive Inference
Masao Someki, Nicholas Eng, Yosuke Higuchi +1
Attention-based encoder-decoder models with autoregressive (AR) decoding have proven to be the dominant approach for automatic speech recognition (ASR) due to their superior accura…
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…
Harnessing the Zero-Shot Power of Instruction-Tuned Large Language Model in End-to-End Speech Recognition
Yosuke Higuchi, Tetsuji Ogawa, Tetsunori Kobayashi
We propose to utilize an instruction-tuned large language model (LLM) for guiding the text generation process in automatic speech recognition (ASR). Modern large language models (L…
A Study on the Integration of Pre-trained SSL, ASR, LM and SLU Models for Spoken Language Understanding
Yifan Peng, Siddhant Arora, Yosuke Higuchi +6
Collecting sufficient labeled data for spoken language understanding (SLU) is expensive and time-consuming. Recent studies achieved promising results by using pre-trained models in…