Acoustic models of the elderly for large-vocabulary continuous speech recognition
Abstract
Abstract Widespread use of large‐vocabulary continuous speech recognition systems has recently occurred, encouraging the application of speech recognition techniques to various problems. One of the factors that adversely affect the performance of speech recognition systems is a mismatch between the acoustic properties of the speech of the system user and the acoustic model. The speech of young or middle‐aged adults is generally used in constructing the acoustic model. Thus, a mismatch occurs between the model and the acoustic properties of the speech of the elderly, which may degrade the recognition rate. In this study, a large‐scale elderly speech database (200 sentences ×301 subjects) is used to train the acoustic model, and the resulting elderly acoustic model is evaluated by using a large‐vocabulary continuous speech recognition system. In the experiments, the word recognition rate was improved by 3 to 5% compared to the recognition results of an acoustic model trained by young or middle‐aged adult speech, namely, by the JNAS speech database (150 sentences ×260 subjects, average 28.6 years). It is also verified experimentally that the recognition rate is further improved in speaker adaptation to elderly speech by making use of an acoustic model trained by elderly speech. © 2004 Wiley Periodicals, Inc. Electron Comm Jpn Pt 2, 87(7): 49–57, 2004; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/ecjb.20101
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As aging decreases the ability to retrieve and recognize words, older users become less sensitive to sounds and take longer to find the right words to express themselves.
“As aging decreases the ability to retrieve and recognize words, older users become less sensitive to sounds and take longer to find the right words to express themselves (Baba et al., 2004).”
From Using Different Error Handling Strategies to Facilitate Older Users' Interaction With Chatbots in Learning Information and Communication Technologies (2021) · cites this paper as Baba et al., 2004
Classical ASR systems exhibit poor performances for older adults' voice.
“Some authors (Baba et al., 2004) have reported that classical ASR systems exhibit poor performances for older adults' voice.”
From Making Emergency Calls More Accessible to Older Adults Through a Hands-free Speech Interface in the House (2019) · cites this paper as Baba et al., 2004
ASR performance degrades for older adults.
“For example, ASR performances degrades for older adults.”
From Making Emergency Calls More Accessible to Older Adults Through a Hands-free Speech Interface in the House (2019) · cites this paper as Baba et al., 2004
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- Authors
- Baba, A., Yoshizawa, S., Yamada, M., Lee, A., & Shikano, K.
- Affiliations
- Panasonic (Japan) (JP)
- Nara Institute of Science and Technology (JP)
- ORCID
- Lee, Akinobu
- Venue
- Electronics and Communications in Japan (Part II Electronics)
- Publisher
- Wiley
- Published
- 2004-06-09
- Volume
- 87
- Issue
- 7
- Pages
- 49-57
- ISSN
- 1520-6432 (ISSN-L)
- 8756-663X
- OpenAlex
- W2044408773
- Cited by
- 45
- References
- 5
- Citations by year
- 2023: 3 · 2021: 2 · 2019: 5 · 2018: 1 · 2016: 1 · 2015: 3 · 2014: 7 · 2013: 4 · 2012: 7
- FWCI
- 0.68
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Electronics and Communications in Japan (Part II Electronics) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Physical Sciences › Computer Science › Signal Processing › Speech and Audio Processing
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Phonetics and Phonology Research
- Keywords
- elderly speech, acoustic modeling, large vocabulary continuous speech recognition, speaker adaptation, speech corpus, word recognition rate
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