4 papers
Speaker-Distinguishable CTC: Learning Speaker Distinction Using CTC for Multi-Talker Speech Recognition
Asahi Sakuma, Hiroaki Sato, Ryuga Sugano +3
This paper presents a novel framework for multi-talker automatic speech recognition without the need for auxiliary information. Serialized Output Training (SOT), a widely used appr…
A Comparative Study on Positional Encoding for Time-frequency Domain Dual-path Transformer-based Source Separation Models
Kohei Saijo, Tetsuji Ogawa
In this study, we investigate the impact of positional encoding (PE) on source separation performance and the generalization ability to long sequences (length extrapolation) in Tra…
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…
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…