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Researcher profile

Takaaki Hori

6 papers in the PaperMetrix corpus

Publications

Papers by this author

  1. Multilingual sequence-to-sequence speech recognition: architecture, transfer learning, and language modeling

    2018 · arXiv (Cornell University)

    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 lexicon and alignments. However, this poses a new problem of requiring more …

  2. Semi-Supervised Speech Recognition Via Graph-Based Temporal Classification

    2021

    Semi-supervised learning has demonstrated promising results in automatic speech recognition (ASR) by self-training using a seed ASR model with pseudo-labels generated for unlabeled data. The effectiveness of this approach largely relies on the pseudo-label accuracy, …

  3. Joint CTC-attention based end-to-end speech recognition using multi-task learning

    2017

    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 attention-based encoder-decoder framework that learns a mapping between variable-length input …

  4. ESPnet: End-to-End Speech Processing Toolkit

    2018 · arXiv (Cornell University)

    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 widely-used dynamic neural network toolkits, Chainer and PyTorch, as a …

  5. Cycle-consistency Training for End-to-end Speech Recognition

    2019

    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 knowledge such as pronunciation dictionaries to build ASR systems, …

  6. A Comparative Study on Transformer vs RNN in Speech Applications

    2019 · 2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)

    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). This paper focuses on an emergent sequence-to-sequence model called Transformer, which achieves state-of-the-art …