min – 80ms max – 142ms attack min - ͠ max - ͠ sustain min – 109ms max – 459ms decay 1....
TRANSCRIPT
•Min – 80ms•Max – 142ms
Attack
•Min - �•Max - �
Sustain•Min – 109ms•Max – 459ms
Decay
1. Introduction
3. Blink Morphology2. Methodology & Results
4. Blink Model
In the ‘Blink’ of an Eye
Recent robotics research progress raises the possibility of the creation of a social cognitive robotic system that resembles the bodily structure of a human, that can communicate effectively utilising human socio-communication metaphors and that can comfortably exist in human social surroundings. Further, it is clearly assumed that any truly useful cognitive social robot will need to be able to effectively communicate with its users [Breazeal 2002; Oestreicher 2007b]. Humans use both verbal and non-verbal modes of communication. Non-verbal facial behaviour transmits the highest impact (55%) of the message being expressed [Koneya and Barbour 1976]. Humans are experts in social interaction, and thus their expectations of any communicative interactions will understandably be extremely high. It seems logical therefore to imbue these social cognitive robotic systems with imitative human communication systems [Breazeal and Scassellati 1999; Cassell et al. 1994; Dautenhahn 2007]. Such systems will allow a human user to monitor and interpret the expressed human-like behaviour and mental communicative states of a social cognitive robotic system and to communicate naturally, based upon this feedback.
Our experimental setup (Fig. 3) was designed to capture human non-verbal facial behaviour utilising dialogues to elicit ‘mental communicative states’ of understanding, uncertainty, misunderstanding and thought (Fig. 4) which are constantly transitioned between during human-human communication. This allowed for transcription and analysis of the facial non-verbal behavioural traits that each of these ‘mental communicative states’ trigger during the communicative process, allowing a detailed model of human-human non-verbal facial behaviour within communication to be analysed and built computationally for use within a social cognitive robotic system.
The morphology of the blink is defined through its type of either half (9%) or full (91%), (where a ‘half’ type is where the eyelid is only half closed when a blink action is performed, it’s duration (in milliseconds), of which the average blink duration is 1/3sec (Fig. 5). The duration is then further broken down into attack (the closing duration of the eyelid), sustain (the duration the eyelid is kept closed) and decay (the re-opening duration of the eyelid) (Fig. 6).
In our blink generation model (Fig. 7), a blink action call is made for each blink trigger related non-verbal facial behaviour dimension instantiated throughout a dialogue interaction with a user. Each facial behaviour dimension is parsed through a weighting process based upon its blink co-occurrence chance %. If a blink occurrence is triggered, all other behaviour dimensions are ignored until the next update function call. The position (or delay) in producing the blink action is defined through the blink position probability curve (Fig. 4) of the triggering behaviour dimension. A physiological blink mechanism (for cleaning/humidifying the eye) [Al-Abdulmunem and Briggs 1999] is also included in the model, , commonly performing a blink action within a timeframe of 1.96 - 10.2sec where no prior blink has been instantiated.
Therefore, the blink model triggers a blink action either on receiving and accepting (based on the specific dimension weighting value of) a behaviour dimension or when a physiological blink is instantiated.
Analysis of our data revealed strong co-occurrence between the human blink process and non-verbal facial behaviour dimensions (Fig. 2) of own speech instigation and completion, interlocutor speech instigation, looking at/away from the interlocutor, facial expression instigation and completion and mental communicative state change. 71% of the total 2007 analysed blinks captured co-occurred with these dimensions (within a time window of +/- 375ms), well beyond their co-occurrence chance probability of 23%, thus we suggest that at least 71% of blinks previously described as "physiological" [Al-Abdulmunem and Briggs 1999] (e.g. for cleaning/humidifying the eye) are actually related directly to human communicative behaviour.
AL-ABDULMUNEM, M.A. AND BRIGGS, S.T. 1999. Spontaneous blink rate of a normal population sample. International Contact Lens Clinic 26, 29-32.BREAZEAL, C. 2002. Designing Sociable Robots. The MIT Press, Cambridge, Massachusetts.BREAZEAL, C. AND SCASSELLATI, B. 1999. How to build robots that make friends and influence people. In Intelligent Robots and Systems, 1999. IROS '99. Proceedings. 1999 IEEE/RSJ International Conference on, 858-863 vol.852.CASSELL, J., PELACHAUD, C., BADLER, N., STEEDMAN, M., ACHORN, B., BECKET, T., DOUVILLE, B., PREVOST, S. AND STONE, M. 1994. Animated conversation: rule-based generation of facial expression, gesture \& spoken intonation for multiple conversational agents. In Proceedings of the Proceedings of the 21st annual conference on Computer graphics and interactive techniques1994 ACM.DAUTENHAHN, K. 2007. Socially intelligent robots: dimensions of human-robot interaction. Philisophical Transactions of the Royal Society, 679-704.KONEYA, M. AND BARBOUR, A. 1976. Louder than words (nonverbal communication). Charles E. Merrill Publishing Company.OESTREICHER, L. 2007b. Cognitive, Social, Sociable or just Socially Acceptable Robots? In Proceedings of the Robot and Human interactive Communication, 2007. RO-MAN 2007. The 16th IEEE International Symposium on 26-29 Aug. 2007 pages: 558 - 563 2007b, 558-563.
Christopher Ford, Dr Guido Bugmann, Dr Phil Culverhouse
Figure. 1. Message Impact Breakdown (Koneya and Barbour, 1976)
Figure. 7. Blink Model (Ford, 2012)
Figure. 5. Avg. Blink Duration (Ford, 2012)
Figure. 6. Blink ASD Morphology (Ford, 2012)Figure. 4. Speech Onset Blink Coverage (Ford, 2012)
Figure. 3. Experimental Setup (Ford, 2012)
WeightingProcess
1.96 to 10.2 sec
REFERENCES: University of Plymouth Graduate School BursaryFUNDING:
Centre for Robotics and Neural Systems,University of Plymouth,Room B106, Portland Square Building,Drake Circus, Plymouth,Devon, PL4 8AA, UK
CONTACT: Tel: +44 (0) 1752 586294E-mail: [email protected]
Figure. 2. Blink co-occurrence with Non-Verbal Facial Behaviour Dimensions (Ford, 2012)