Perspectives on Speech and Language Interaction for Daily Assistive Technology

doi:10.1145/2791576

ACM Trans. Access. Comput.

2015

DOI: 10.1145/2791576

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Perspectives on Speech and Language Interaction for Daily Assistive Technology

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Cited by 2 publications

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Distant speech processing for smart home: comparison of ASR approaches in scattered microphone network for voice command

Lecouteux

Vacher

Portet

2018

Int J Speech Technol

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Voice command in multi-room smart homes for assisting people in loss of autonomy in their daily activities faces several challenges, one of them being the distant condition which impacts ASR performance. This paper presents an overview of multiple techniques for fusion of multi-source audio (pre, middle, post fusion) for automatic speech recognition for in-home voice command. The robustness of the models of speech is obtained by adaptation to the environment and to the task. Experiments are based on several publicly available realistic datasets with participants enacting activities of daily life. The corpora were recorded in natural condition, meaning background noise is sporadic, so there is no extensive background noise in the data. The smart home is equipped with one or two microphones in each room, the distance between them being larger than 1 meter. An evaluation of the most suited techniques improves voice command recognition at the decoding level, by using multiple sources and model adaptation. Although Word Error Rate (WER) is between 26% and 40%, Domotic Error Rate (identical to the WER, but at the level of the voice command) is less than 5.8% for deep neural network models, the method using Feature space Maximum Likelihood Linear Regression (fMLLR) with speaker adaptation training and Subspace Gaussian Mixture Model (SGMM) exhibits comparable results.

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Distant speech processing for smart home: comparison of ASR approaches in scattered microphone network for voice command

Lecouteux

Vacher

Portet

2018

Int J Speech Technol

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Making Emergency Calls More Accessible to Older Adults Through a Hands-free Speech Interface in the House

Vacher

Aman

Rossato

et al. 2019

ACM Trans. Access. Comput.

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Wearable personable emergency response (PER) systems are the mainstream solution for allowing frail and isolated individuals to call for help in an emergency. However, these devices are not well adapted to all users and are often not worn all the time, meaning they are not available when needed. This paper presents a Voice User Interface system for emergency call recognition. The interface is designed to permit hands-free interaction using natural language. Crucially, this allows a call for help to be registered without necessitating physical proximity to the system. The system is based on an ASR engine and is tested on a corpus collected to simulate realistic situations. The corpus contains French speech from 4 older adults and 13 younger people wearing an old-age simulator to hamper their mobility, vision and hearing. On-line evaluation of the preliminary system showed an emergency call error rate of 27%. Subsequent off-line experimentation improved the results (call error rate 24%), demonstrating that emergency call recognition in the home is achievable. Another contribution of this work is the corpus, which is made available for research with the hope that it will facilitate related research and quicker development of robust methods for automatic emergency call recognition in the home.

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Perspectives on Speech and Language Interaction for Daily Assistive Technology

Cited by 2 publications

References 24 publications

Distant speech processing for smart home: comparison of ASR approaches in scattered microphone network for voice command

Distant speech processing for smart home: comparison of ASR approaches in scattered microphone network for voice command

Making Emergency Calls More Accessible to Older Adults Through a Hands-free Speech Interface in the House

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