Speech recognition of aged voice in the AAL context: Detection of distress sentences
Abstract
By 2050, about a third of the French population will be over 65. In the context of technologies development aiming at helping aged people to live independently at home, the CIRDO project aims at implementing an ASR system into a social inclusion product designed for elderly people in order to detect distress situations. Speech recognition systems present higher word error rate when speech is uttered by elderly speakers compared to when non-aged voice is considered. Two specialized corpora in French, AD80 and ERES38, were recorded in this framework by aged people, they were used first to study the possibility of adaptation of standard ASR to aged voice. Then we looked at whether the variability of the WER between speakers could be correlated with the level of dependence. Then, we assessed the performance of distress sentence detection by a filter and we demonstrated a significant drop in performance for those with the lowest degree of autonomy.
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Performance in automatic speech recognition dropped significantly when users were disabled older adults.
“Aman et al. [51] have demonstrated that performance in automatic speech recognition dropped significantly when users were disabled older adults, which are the ones who need assistive technologies the most.”
From Usability assessment of interaction management support in LOUISE, an ECA-based user interface for elders with cognitive impairment (2018) · cites this paper as [51]
Cites
Acoustic models of the elderly for large-vocabulary continuous speech recognition
Baba, A., Yoshizawa, S., Yamada, M., Lee, A., & Shikano, K. (2004) · Electronics and Communications in Japan (Part II Electronics) · doi:10.1002/ecjb.20101 · Cited by 45 · see citing works
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Wargnier, P., Benveniste, S., Jouvelot, P., & Rigaud, A.-S. (2018) · Technology and Disability · doi:10.3233/tad-180189 · Cited by 32 · see citing works
Vacher, M., Aman, F., Rossato, S., Portet, F., & Lecouteux, B. (2019) · ACM Transactions on Accessible Computing · doi:10.1145/3310132 · Cited by 10 · see citing works
Self-citation
- Authors
- Aman, F., Vacher, M., Rossato, S., & Portet, F.
- Affiliations
- Université Pierre Mendès France (FR)
- Venue
- 2013 7th Conference on Speech Technology and Human - Computer Dialogue (SpeD)
- Publisher
- IEEE
- Published
- 2013-10
- Pages
- 1-8
- OpenAlex
- W2048978357
- Cited by
- 20
- References
- 1
- Citations by year
- 2022: 2 · 2020: 2 · 2019: 5 · 2018: 3 · 2016: 3 · 2015: 3 · 2014: 2
- FWCI
- 1.72
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Speech Technology and Human-Computer Dialogue (SpeD) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Physical Sciences › Computer Science › Signal Processing › Speech and Audio Processing
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Keywords
- speech recognition, elderly speakers, assistive living, distress detection, word error rate, dependency level, speech variation, French speech, independent living
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