2 citations · 4 across the 11 of their papers we have counts for
11 papers
End-to-End Rich Transcription-Style Automatic Speech Recognition with Semi-Supervised Learning
Tomohiro Tanaka, Ryo Masumura, Mana Ihori +3
We propose a semi-supervised learning method for building end-to-end rich transcription-style automatic speech recognition (RT-ASR) systems from small-scale rich transcription-styl…
Cross-Modal Transformer-Based Neural Correction Models for Automatic Speech Recognition
Tomohiro Tanaka, Ryo Masumura, Mana Ihori +5
We propose a cross-modal transformer-based neural correction models that refines the output of an automatic speech recognition (ASR) system so as to exclude ASR errors. Generally,…
Unified Autoregressive Modeling for Joint End-to-End Multi-Talker Overlapped Speech Recognition and Speaker Attribute Estimation
Ryo Masumura, Daiki Okamura, Naoki Makishima +4
In this paper, we present a novel modeling method for single-channel multi-talker overlapped automatic speech recognition (ASR) systems. Fully neural network based end-to-end model…
Enrollment-less training for personalized voice activity detection
Naoki Makishima, Mana Ihori, Tomohiro Tanaka +3
We present a novel personalized voice activity detection (PVAD) learning method that does not require enrollment data during training. PVAD is a task to detect the speech segments…
Zero-Shot Joint Modeling of Multiple Spoken-Text-Style Conversion Tasks using Switching Tokens
Mana Ihori, Naoki Makishima, Tomohiro Tanaka +3
In this paper, we propose a novel spoken-text-style conversion method that can simultaneously execute multiple style conversion modules such as punctuation restoration and disfluen…
Audio-Visual Speech Separation Using Cross-Modal Correspondence Loss
Naoki Makishima, Mana Ihori, Akihiko Takashima +3
We present an audio-visual speech separation learning method that considers the correspondence between the separated signals and the visual signals to reflect the speech characteri…