1. The production of a reminiscing conversational agent and the
implementation of an ontology of reminiscence
Collette Curry, James O’Shea, Keeley Crockett and Laura BrownBackground
In 2008, 1.3 million people in the United Kingdom were
aged 85 and over; this number is projected to reach 3.3
million by 2033 [1]. Aging memory impairment problems
will become more acute as the population profile
changes [1]. Improvement of memory impairment
reduces distress and enhances an individual’s wellbeing
and independence [2:3]. Quality of life in old age can
also be improved by increased subjective well-being,
which is concerned with how people experience their
lives, and includes both emotional reactions and
cognitive judgments [4].
Why Reminiscence?
Reminiscence concerns telling stories of the past,
personal histories, individual perceptions of social
worlds inhabited, and events experienced personally or
at a distance [5]. Bender [9] provides a wide range of
twenty possible purposes and benefits that can derive
from reminiscence. Using a three-Cs model, these
include
1) benefits for clients, such as interacting, socializing,
learning and engaging in therapeutic activities;
2) benefits for carers to aid communication and
improve staff skills;
3) benefits for the work context or culture of the unit [9].
Since publication of the Life Review paper by Butler [5]
there has been an exponential growth in literature
concerning reminiscence and life review, making the
importance of reminiscence and life review in the caring
services clear.
Betty speaks to the
user and responds to
enquiries with
seeming intelligence.
Objectives
There are many different algorithms available to produce
conversational agents, using a variety of computer
languages, databases and flat text files. The study
explored these different algorithms and proposed a
method that utilised a database as well as an ontology of
reminiscence to provide faster and more realistic
conversation in the reminiscence domain.
Results
Usability of the system was checked with a small sample of
participants and the system modified accordingly. This
research conducted a comparative usability test to explore
that a CA effectively contributed to reminiscence in terms of
its functionality and interface and did not create more
problems than it solved. This was done by separate use of a
web based questionnaire compared with the same questions
during a conversation with ‘Betty’.
Future evaluation of the CA ‘Betty’ will be by the use of a
general anxiety and depression scale which will test well-
being of the person both before and after application of the
CA. In addition, the use of standard instruments such as the
Everyday Memory Questionnaire (EMQ) [10] both before and
after the application of the CA will inform whether there is a
noticeable difference in cognitive ability after use of the CA.
Standard instruments can be used to screen for cognitive
impairment. They can estimate the severity of cognitive
impairment at a specific time and to follow the course of
cognitive changes in an individual over time, thus making
these instruments an effective way to document an
individual's response to any intervention. The EMQ is used
as a subjective measure of memory failure in everyday life.
This more direct assessment of the errors experienced by
older adults during their daily activities may be more useful
for directing the research into developing an intervention that
will have a practical impact. Well-being can be tested with a
range of mood assessment techniques including self-
reporting measures. These could be collected to show levels
of satisfaction with the system.
Methodology
The CA was given a voice using a Text to Speech
system. The web interface was built in Flash using
Action-script 3. It was implemented using HTML5 and
tested on Linux, Windows and Apple systems.
Contact:
Collette Curry collette.curry@mmu.ac.uk
Manchester Metropolitan University, Room E113, John Dalton Building, Chester Street. Manchester M1 5GD
Adaptive narrative
The ability to generate narrative is of importance to computer
systems that wish to use reminiscence effectively for a wide
range of contexts ranging from entertainment to training and
education. The typical approach for incorporating narrative
into a computer system is for system builders to script the
narrative features at design time. This CA uses an ontology
to propagate the content and learns from the conversation
logs using keywords.
An ontology of
reminiscence was drawn
up and used with Betty.
Ontology of Reminiscence
The CA system consists of data imported from WordNet with a
reminiscence ontology. The definition of meaning in WordNet is words
that are synonyms in some particular context. Such a collection in
WordNet is called a synset. Since words can have multiple meanings
(and be multiple parts of speech), the flags of a word are a summary of
all of the properties it might have and it has a list of entries called
"meanings". Each entry is a meaning and points to the circular list, one of
which marks the word you land at as the synset head. This is referred to
as the "master" meaning and has the gloss (definition) of the meaning.
The meaning list of a master node points back to all the real words which
comprise it.
Since WordNet has an ontology, its synsets are hooked to other synsets
in various relations, particular that of parent and child. The CA
represents these as facts. The hierarchical relationship uses the verb "is"
and has the child as subject and the parent as object.
Conclusions
Using the ‘Betty’ package, older adults took part in
reminiscence themed conversations. Conversations were
logged and used to create personal dictionaries and themes
for further future conversation. The CA was able to acquire
new knowledge in this way. The ontology grew as the
participant related more information during the conversation
Aims
To produce an ontology of reminiscence that can be
used to inform the knowledgebase of a conversational
agent (CA) called ‘Betty’. This will then be used as a
reminiscence aid for people with aging memory loss as
part of normal aging.
The ontology is
linked to WordNet.
Ontology
hierarchy References
1 Stockport Metropolitan Borough Council (2010), Dementia: Strategy Document.
[Online] [Accessed on 12th January 2012]
2 Dorin, M. (2007) ‘Online education of older adults and its relation to life
satisfaction’. Educational Gerontology, 33(2), 127-143.
3 Wagner, N., Hassanein, K. and Head, M. (2010) ‘Computer use by older adults. A
multi-disciplinary review’. Computers in Human Behaviour, 26, 870-882
4 George, L. K (2010) Still happy after all these years: Research frontiers on
subjective well-being in later life. The Journal of Gerontology Series B,
Psychological Sciences and Social Sciences. 65B(3):331-9. doi:
10.1093/geronb/gbq006.
5 Butler, R.N.(1963) The Life Review: An interpretation of reminiscence in the aged.
Psychiatry, 26: 65-76.
6 Trueman, I. and Parker, J. (2004) Life review in palliative care. European journal of
palliative care, 11(6): 249-53.
7 Parker, J. (2003) Positive communication with people who have dementia. In:
Adams, T. and Manthorpe, J. (eds.). Dementia Care. London: Arnold, pp.148-63.
8 WordNet: An electronic lexical database available from Princeton University
[online] http://wordnet.princeton.edu/wordnet/ [Accessed 20th December 2012]
9 Bender, M., Bauckham, P. & Norris, A., 1999. The therapeutic purposes of
reminiscence. London: Sage.
10 Sunderland, A., Harris, J.E., & Baddeley, A, (1983) The Everyday Memory
Questionnaire
The ontology began as a list of facets and developed through several iterations. In the example it can be seen that
classes have properties and relationships.
The CA has a standard response mechanism to deal with off-topic
user utterances. This is known as the ELIZA layer.
The CA began life as a text block which displayed the CA
response as well as the user’s input. The CA remembered
past visits and conversations
Future work
The CA ‘Betty’ could be contained in a multi-activity environment.
Games and other challenges could be provided as well as email and
personal photo album access.
Improvement of mood can result from speaking with the CA
NLDB-2013
Salford University
Media City
The CA evolved into a speaking avatar, displaying the user utterance and CA response as text on the screen. This helped
with reinforcement of the conversation.