788 citations · 1.1k across the 33 of their papers we have counts for
17 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…
Audio-Visual Scene-Aware Dialog and Reasoning using Audio-Visual Transformers with Joint Student-Teacher Learning
Ankit P. Shah, Shijie Geng, Peng Gao +5
In previous work, we have proposed the Audio-Visual Scene-Aware Dialog (AVSD) task, collected an AVSD dataset, developed AVSD technologies, and hosted an AVSD challenge track at bo…
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…
Unsupervised Domain Adaptation for Speech Recognition via Uncertainty Driven Self-Training
Sameer Khurana, Niko Moritz, Takaaki Hori +1
The performance of automatic speech recognition (ASR) systems typically degrades significantly when the training and test data domains are mismatched. In this paper, we show that s…
Multi-Pass Transformer for Machine Translation
Peng Gao, Chiori Hori, Shijie Geng +2
In contrast with previous approaches where information flows only towards deeper layers of a stack, we consider a multi-pass transformer (MPT) architecture in which earlier layers…
A Comparative Study on Transformer vs RNN in Speech Applications
Shigeki Karita, Nanxin Chen, Tomoki Hayashi +10
Sequence-to-sequence models have been widely used in end-to-end speech processing, for example, automatic speech recognition (ASR), speech translation (ST), and text-to-speech (TTS…
Multi-encoder multi-resolution framework for end-to-end speech recognition
Ruizhi Li, Xiaofei Wang, Sri Harish Mallidi +3
Attention-based methods and Connectionist Temporal Classification (CTC) network have been promising research directions for end-to-end Automatic Speech Recognition (ASR). The joint…
Stream attention-based multi-array end-to-end speech recognition
Xiaofei Wang, Ruizhi Li, Sri Harish Mallid +3
Automatic Speech Recognition (ASR) using multiple microphone arrays has achieved great success in the far-field robustness. Taking advantage of all the information that each array…
Cycle-consistency training for end-to-end speech recognition
Takaaki Hori, Ramon Astudillo, Tomoki Hayashi +3
This paper presents a method to train end-to-end automatic speech recognition (ASR) models using unpaired data. Although the end-to-end approach can eliminate the need for expert k…
Multilingual sequence-to-sequence speech recognition: architecture, transfer learning, and language modeling
Jaejin Cho, Murali Karthick Baskar, Ruizhi Li +6
Sequence-to-sequence (seq2seq) approach for low-resource ASR is a relatively new direction in speech research. The approach benefits by performing model training without using lexi…
End-to-end Speech Recognition with Word-based RNN Language Models
Takaaki Hori, Jaejin Cho, Shinji Watanabe
This paper investigates the impact of word-based RNN language models (RNN-LMs) on the performance of end-to-end automatic speech recognition (ASR). In our prior work, we have propo…
Back-Translation-Style Data Augmentation for End-to-End ASR
Tomoki Hayashi, Shinji Watanabe, Yu Zhang +4
In this paper we propose a novel data augmentation method for attention-based end-to-end automatic speech recognition (E2E-ASR), utilizing a large amount of text which is not paire…
End-to-End Audio Visual Scene-Aware Dialog using Multimodal Attention-Based Video Features
Chiori Hori, Huda Alamri, Jue Wang +10
Dialog systems need to understand dynamic visual scenes in order to have conversations with users about the objects and events around them. Scene-aware dialog systems for real-worl…
ESPnet: End-to-End Speech Processing Toolkit
Shinji Watanabe, Takaaki Hori, Shigeki Karita +9
This paper introduces a new open source platform for end-to-end speech processing named ESPnet. ESPnet mainly focuses on end-to-end automatic speech recognition (ASR), and adopts w…
Advances in Joint CTC-Attention based End-to-End Speech Recognition with a Deep CNN Encoder and RNN-LM
Takaaki Hori, Shinji Watanabe, Yu Zhang +1
We present a state-of-the-art end-to-end Automatic Speech Recognition (ASR) model. We learn to listen and write characters with a joint Connectionist Temporal Classification (CTC)…
End-to-end Conversation Modeling Track in DSTC6
Chiori Hori, Takaaki Hori
End-to-end training of neural networks is a promising approach to automatic construction of dialog systems using a human-to-human dialog corpus. Recently, Vinyals et al. tested neu…
Joint CTC-Attention based End-to-End Speech Recognition using Multi-task Learning
Suyoun Kim, Takaaki Hori, Shinji Watanabe
Recently, there has been an increasing interest in end-to-end speech recognition that directly transcribes speech to text without any predefined alignments. One approach is the att…