788 citations · 887 across the 15 of their papers we have counts for
8 papers · 1 filter
FLEURS-R: A Restored Multilingual Speech Corpus for Generation Tasks
Min Ma, Yuma Koizumi, Shigeki Karita +4
This paper introduces FLEURS-R, a speech restoration applied version of the Few-shot Learning Evaluation of Universal Representations of Speech (FLEURS) corpus. FLEURS-R maintains…
Lenient Evaluation of Japanese Speech Recognition: Modeling Naturally Occurring Spelling Inconsistency
Shigeki Karita, Richard Sproat, Haruko Ishikawa
Word error rate (WER) and character error rate (CER) are standard metrics in Speech Recognition (ASR), but one problem has always been alternative spellings: If one's system transc…
Knowledge Transfer from Large-scale Pretrained Language Models to End-to-end Speech Recognizers
Yotaro Kubo, Shigeki Karita, Michiel Bacchiani
End-to-end speech recognition is a promising technology for enabling compact automatic speech recognition (ASR) systems since it can unify the acoustic and language model into a si…
A Comparative Study on Neural Architectures and Training Methods for Japanese Speech Recognition
Shigeki Karita, Yotaro Kubo, Michiel Adriaan Unico Bacchiani +1
End-to-end (E2E) modeling is advantageous for automatic speech recognition (ASR) especially for Japanese since word-based tokenization of Japanese is not trivial, and E2E modeling…
Unsupervised Learning of Disentangled Speech Content and Style Representation
Andros Tjandra, Ruoming Pang, Yu Zhang +1
We present an approach for unsupervised learning of speech representation disentangling contents and styles. Our model consists of: (1) a local encoder that captures per-frame info…
ESPnet-ST: All-in-One Speech Translation Toolkit
Hirofumi Inaguma, Shun Kiyono, Kevin Duh +4
We present ESPnet-ST, which is designed for the quick development of speech-to-speech translation systems in a single framework. ESPnet-ST is a new project inside end-to-end speech…
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…
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…