3 citations · 9 across the 15 of their papers we have counts for
14 papers
On the Use of Modality-Specific Large-Scale Pre-Trained Encoders for Multimodal Sentiment Analysis
Atsushi Ando, Ryo Masumura, Akihiko Takashima +6
This paper investigates the effectiveness and implementation of modality-specific large-scale pre-trained encoders for multimodal sentiment analysis~(MSA). Although the effectivene…
Audio Visual Scene-Aware Dialog Generation with Transformer-based Video Representations
Yoshihiro Yamazaki, Shota Orihashi, Ryo Masumura +2
There have been many attempts to build multimodal dialog systems that can respond to a question about given audio-visual information, and the representative task for such systems i…
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…