3 accepted papers
This paper investigates cascade approaches bridging speech and text foundation models (FMs) for speech translation (ST). We address the limitations of cascade systems which suffer from the propagation of speech recognition errors and the lack of access to acoustic information. We propose a ReShape A…
This paper proposes a novel speech emotion recognition (SER) method that fully leverages the architecture of Whisper, a large-scale automatic speech recognition (ASR) model. The conventional SER models using a pre-trained speech encoder may fail to capture linguistic content since their decoders are…
It remains a question that how simultaneous interpretation (SI) data affects simultaneous machine translation (SiMT). Research has been limited due to the lack of a large-scale training corpus. In this work, we aim to fill in the gap by introducing NAIST-SIC-Aligned, which is an automatically-aligne…