本文へ移動

論文 ·日本語 ·未確認

A New Corpus of Elderly Japanese Speech for Acoustic Modeling, and a Preliminary Investigation of Dialect-Dependent Speech Recognition

Meiko Fukuda Ryota Nishimura Hiromitsu Nishizaki Yurie Iribe Norihide Kitaoka

刊行年
2019-10-01
言語
英語
OpenAlex
W3011453267
DOI
10.1109/o-cocosda46868.2019.9041216
MAG
3011453267
URL
https://doi.org/10.1109/o-cocosda46868.2019.9041216

要旨

We have constructed a new speech data corpus consisting of the utterances of 221 elderly Japanese people (average age: 79.2) with the aim of improving the accuracy of automatic speech recognition (ASR) for the elderly. ASR is a beneficial modality for people with impaired vision or limited hand movement, including the elderly. However, speech recognition systems using standard recognition models, especially acoustic models, have been unable to achieve satisfactory performance for the elderly. Thus, creating more accurate acoustic models of the speech of elderly users is essential for improving speech recognition for the elderly. Using our new corpus, which includes the speech of elderly people living in three regions of Japan, we conducted speech recognition experiments using a variety of DNN-HNN acoustic models. As training data for our acoustic models, we examined whether a standard adult Japanese speech corpus (JNAS), an elderly speech corpus (S-JNAS) or a spontaneous speech corpus (CSJ) was most suitable, and whether or not adaptation to the dialect of each region improved recognition results. We adapted each of our three acoustic models to all of our speech data, and then re-adapt them using speech from each region. Without adaptation, the best recognition results were obtained when using the S-JNAS trained acoustic models (total corpus: 21.85% Word Error Rate). However, after adaptation of our acoustic models to our entire corpus, the CSJ trained models achieved the lowest WERs (entire corpus: 17.42%). Moreover, after readaptation to each regional dialect, the CSJ trained acoustic model with adaptation to regional speech data showed tendencies of improved recognition rates. We plan to collect more utterances from all over Japan, so that our corpus can be used as a key resource for elderly speech recognition in Japanese. We also hope to achieve further improvement in recognition performance for elderly speech.

主題

この書誌の出所

  • openalex— W3011453267(2026-08-14取得)

引用

Meiko Fukuda・Ryota Nishimura・Hiromitsu Nishizaki・Yurie Iribe・Norihide Kitaoka(2019-10-01) A New Corpus of Elderly Japanese Speech for Acoustic Modeling, and a Preliminary Investigation of Dialect-Dependent Speech Recognition pp. 1-6

Fukuda2019NewCorpusElderly
書誌 67,320件 語別索引 17,251件 資源 113件 研究者 303名 JSON