6 citations · 19 across the 22 of their papers we have counts for
6 papers · 1 filter
Sequence Transduction with Graph-based Supervision
Niko Moritz, Takaaki Hori, Shinji Watanabe +1
The recurrent neural network transducer (RNN-T) objective plays a major role in building today's best automatic speech recognition (ASR) systems for production. Similarly to the co…
Advancing Momentum Pseudo-Labeling with Conformer and Initialization Strategy
Yosuke Higuchi, Niko Moritz, Jonathan Le Roux +1
Pseudo-labeling (PL), a semi-supervised learning (SSL) method where a seed model performs self-training using pseudo-labels generated from untranscribed speech, has been shown to e…
Dual Causal/Non-Causal Self-Attention for Streaming End-to-End Speech Recognition
Niko Moritz, Takaaki Hori, Jonathan Le Roux
Attention-based end-to-end automatic speech recognition (ASR) systems have recently demonstrated state-of-the-art results for numerous tasks. However, the application of self-atten…
Momentum Pseudo-Labeling for Semi-Supervised Speech Recognition
Yosuke Higuchi, Niko Moritz, Jonathan Le Roux +1
Pseudo-labeling (PL) has been shown to be effective in semi-supervised automatic speech recognition (ASR), where a base model is self-trained with pseudo-labels generated from unla…
Advanced Long-context End-to-end Speech Recognition Using Context-expanded Transformers
Takaaki Hori, Niko Moritz, Chiori Hori +1
This paper addresses end-to-end automatic speech recognition (ASR) for long audio recordings such as lecture and conversational speeches. Most end-to-end ASR models are designed to…
Capturing Multi-Resolution Context by Dilated Self-Attention
Niko Moritz, Takaaki Hori, Jonathan Le Roux
Self-attention has become an important and widely used neural network component that helped to establish new state-of-the-art results for various applications, such as machine tran…