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Development of an automated speech recognition interface for Personal Emergency Response Systems.

Hamill M, Young V, Boger J, Mihailidis A - J Neuroeng Rehabil (2009)

Bottom Line: If occupants do not wear the push button or cannot access the button, then the system is useless in the event of a fall or emergency.Testing compared a single microphone versus a microphone array with nine adults in both noisy and quiet conditions.In all cases, dialog testing resulted in the system reaching the correct decision about the kind of assistance the user was requesting.

View Article: PubMed Central - HTML - PubMed

Affiliation: The Institute of Biomaterials and Biomedical Engineering, University of Toronto, ON, Canada. melinda.mclean@utoronto.ca

ABSTRACT

Background: Demands on long-term-care facilities are predicted to increase at an unprecedented rate as the baby boomer generation reaches retirement age. Aging-in-place (i.e. aging at home) is the desire of most seniors and is also a good option to reduce the burden on an over-stretched long-term-care system. Personal Emergency Response Systems (PERSs) help enable older adults to age-in-place by providing them with immediate access to emergency assistance. Traditionally they operate with push-button activators that connect the occupant via speaker-phone to a live emergency call-centre operator. If occupants do not wear the push button or cannot access the button, then the system is useless in the event of a fall or emergency. Additionally, a false alarm or failure to check-in at a regular interval will trigger a connection to a live operator, which can be unwanted and intrusive to the occupant. This paper describes the development and testing of an automated, hands-free, dialogue-based PERS prototype.

Methods: The prototype system was built using a ceiling mounted microphone array, an open-source automatic speech recognition engine, and a 'yes' and 'no' response dialog modelled after an existing call-centre protocol. Testing compared a single microphone versus a microphone array with nine adults in both noisy and quiet conditions. Dialogue testing was completed with four adults.

Results and discussion: The microphone array demonstrated improvement over the single microphone. In all cases, dialog testing resulted in the system reaching the correct decision about the kind of assistance the user was requesting. Further testing is required with elderly voices and under different noise conditions to ensure the appropriateness of the technology. Future developments include integration of the system with an emergency detection method as well as communication enhancement using features such as barge-in capability.

Conclusion: The use of an automated dialog-based PERS has the potential to provide users with more autonomy in decisions regarding their own health and more privacy in their own home.

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Related in: MedlinePlus

Flow diagram of system dialog.
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Related In: Results  -  Collection

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Figure 2: Flow diagram of system dialog.

Mentions: Actions are selected through a dialog exchange between the user and the system. The dialog structure for the prototype is depicted in Figure 2. Human factors experiments conducted on computer voice-based systems have demonstrated highest user satisfaction when automated dialog is modelled after live operators [16]. Thus, the prompts have been developed to emulate the familiar and friendly tone of PERS operators, for example, by the use of personal pronouns ("would you like me to call someone else to help you?"), and pre-recording the names of the occupant and responders.


Development of an automated speech recognition interface for Personal Emergency Response Systems.

Hamill M, Young V, Boger J, Mihailidis A - J Neuroeng Rehabil (2009)

Flow diagram of system dialog.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2713250&req=5

Figure 2: Flow diagram of system dialog.
Mentions: Actions are selected through a dialog exchange between the user and the system. The dialog structure for the prototype is depicted in Figure 2. Human factors experiments conducted on computer voice-based systems have demonstrated highest user satisfaction when automated dialog is modelled after live operators [16]. Thus, the prompts have been developed to emulate the familiar and friendly tone of PERS operators, for example, by the use of personal pronouns ("would you like me to call someone else to help you?"), and pre-recording the names of the occupant and responders.

Bottom Line: If occupants do not wear the push button or cannot access the button, then the system is useless in the event of a fall or emergency.Testing compared a single microphone versus a microphone array with nine adults in both noisy and quiet conditions.In all cases, dialog testing resulted in the system reaching the correct decision about the kind of assistance the user was requesting.

View Article: PubMed Central - HTML - PubMed

Affiliation: The Institute of Biomaterials and Biomedical Engineering, University of Toronto, ON, Canada. melinda.mclean@utoronto.ca

ABSTRACT

Background: Demands on long-term-care facilities are predicted to increase at an unprecedented rate as the baby boomer generation reaches retirement age. Aging-in-place (i.e. aging at home) is the desire of most seniors and is also a good option to reduce the burden on an over-stretched long-term-care system. Personal Emergency Response Systems (PERSs) help enable older adults to age-in-place by providing them with immediate access to emergency assistance. Traditionally they operate with push-button activators that connect the occupant via speaker-phone to a live emergency call-centre operator. If occupants do not wear the push button or cannot access the button, then the system is useless in the event of a fall or emergency. Additionally, a false alarm or failure to check-in at a regular interval will trigger a connection to a live operator, which can be unwanted and intrusive to the occupant. This paper describes the development and testing of an automated, hands-free, dialogue-based PERS prototype.

Methods: The prototype system was built using a ceiling mounted microphone array, an open-source automatic speech recognition engine, and a 'yes' and 'no' response dialog modelled after an existing call-centre protocol. Testing compared a single microphone versus a microphone array with nine adults in both noisy and quiet conditions. Dialogue testing was completed with four adults.

Results and discussion: The microphone array demonstrated improvement over the single microphone. In all cases, dialog testing resulted in the system reaching the correct decision about the kind of assistance the user was requesting. Further testing is required with elderly voices and under different noise conditions to ensure the appropriateness of the technology. Future developments include integration of the system with an emergency detection method as well as communication enhancement using features such as barge-in capability.

Conclusion: The use of an automated dialog-based PERS has the potential to provide users with more autonomy in decisions regarding their own health and more privacy in their own home.

Show MeSH
Related in: MedlinePlus