Are Mobile In-Car Communication Systems                Feasible?             A Usability Study                            ...
Agenda•   Introduction•   In-Car Communication Systems (ICCS)•   Speech User Interfaces (SUI)•   Design and Implementation...
Introduction• Driver distraction can be caused by the use of mobile  phone• Sending text messages affects the driver the m...
In-Car Communication Systems (ICCS)• ICCS are a subset of In-Vehicle Infotainment  Systems (IVIS):  – Sending/Receiving te...
Speech User Interface (SUI)• Speech UI or Voice UIs:   – Allows interaction with systems through speech   – Widely used in...
Proposed Design (MIMIC)        Input Module                                                   Output Module               ...
Dialogue Module• Frame approach:  – CALL(number),  – SMS(number, content),  – REDIAL, REPEAT and CANCEL• Prompts user (SMS...
Implementation• Speech engine:   – Google’s cloud-based speech recogniser   – RecognitionListener’s library fully hands-fr...
User Study• Selection of participants:   – 10 participants: students from 18 to 28 year old   – 95 % of usability issues c...
Task ListID                               Task Description      Please call the contact MariaT01   Send the text message  ...
Number of Errors5.004.504.00                          3.003.503.00                                                        ...
Time-on-task Results300250200150100 50  0      T01   T02        T03             T04             T05   T06   T07           ...
Task Completion and Success Rate   ID    Completion     Success   T01        10             9   T02        10             ...
Workload NASA TLX5.004.504.00                                                            3.50                             ...
User Satisfaction Results      Lot of learning needed                                 1.00               Cumbersome       ...
Self-reported metrics on the SUI654                                                                                       ...
Conclusion and Future work• Mobile SUI can only be useful if there are few  usability issues and recognition rate is high....
Thank You               Contact:Emails:   Patrick.TchankueSielinou@nmmu.ac.za          Janet.Wesson@nmmu.ac.za          Di...
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Are Mobile In-Car Communication Systems Feasible? A Usability Study

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Are Mobile In-Car Communication Systems Feasible? A Usability Study

  1. 1. Are Mobile In-Car Communication Systems Feasible? A Usability Study Authors: Patrick Tchankue, Janet Wesson and Dieter Vogts SAICSIT 12, October 1–3, 2012, Centurion, Tshwane, South Africa
  2. 2. Agenda• Introduction• In-Car Communication Systems (ICCS)• Speech User Interfaces (SUI)• Design and Implementation• User Study• Results• Conclusion & Future work
  3. 3. Introduction• Driver distraction can be caused by the use of mobile phone• Sending text messages affects the driver the most• Text messaging increases the crash risk by a factor of 23• Mobile speech user interface (SUI) are one of the proposed solutions• But the usability of mobile SUI has not been widely investigated 1 / 15
  4. 4. In-Car Communication Systems (ICCS)• ICCS are a subset of In-Vehicle Infotainment Systems (IVIS): – Sending/Receiving text messages – Making/Answering calls• Limited access in developing countries: – Limited to several car models – Involve extra costs: e.g. Ford’s SYNC: $395• Examples: – DriveSafe.ly, VoiceTalk, S Voice, Siri 2 / 15
  5. 5. Speech User Interface (SUI)• Speech UI or Voice UIs: – Allows interaction with systems through speech – Widely used in multitasking situations (e.g. Car, Kitchen) – Guarantee eyes-free and hands-free interactions Text-To-Speech Language generation Dialogue manager Database Speech recognition Language understanding Typical architecture for voice-activated application 3 / 15
  6. 6. Proposed Design (MIMIC) Input Module Output Module 1 Text-To-Speech Natural LanguageAutomatic Speech Sensors (TTS) Generation Recognition 9 8 GPS Web servicesNatural Language 2 3 Understanding Dialogue Module 6 Dialogue manager 7 Input pre-processing 4 and Data fusion Context-aware module Frames Peer’s phone 5 4 / 15
  7. 7. Dialogue Module• Frame approach: – CALL(number), – SMS(number, content), – REDIAL, REPEAT and CANCEL• Prompts user (SMS)• Grounding to handle uncertainty• Confirmation before execution 5 / 15
  8. 8. Implementation• Speech engine: – Google’s cloud-based speech recogniser – RecognitionListener’s library fully hands-free• Natural Language Understanding: – Commands, keywords, homophones and synonyms• Text To Speech: – Native Android text-to-speech – Female voice, normal pitch and rate – Samsung Galaxy SII 6 / 15
  9. 9. User Study• Selection of participants: – 10 participants: students from 18 to 28 year old – 95 % of usability issues can be found (Nielsen & Landauer, 1993)• Apparatus and Procedure: – Lane Change Test – Android phone – Steering wheel and pedals• Metrics: – Workload – Time-on-task in seconds – Error on task – Task completion – Success rate. 7 / 15
  10. 10. Task ListID Task Description Please call the contact MariaT01 Send the text message - Say “Call Maria” “I will call you when I get there” to Peter: - Say “Text Peter” - Answer “Yes”T05 - Say ”One” to choose the first option - Say “Yes” to send the selected text message Send the text message “I am running a few minutes late” to John: - Say “SMS John”T02 - Say ”three” to choose the third option Send the text message “I can’t talk text message driving” to Janet: - Say “Yes” to send the selected right now, I am - Say “SMS Janet”T06 - Say “Two” to choose the call: Redial the previous outgoing second optionT03 - Say “Redial” confirm the message “Yes” to - Answer “Yes” Call a number : Please call DianaT07T04 - Say “Call 074 456 1245” - Say “Phone Diana” - Say “Yes” to confirm the number - Answer “Yes” 8 / 15
  11. 11. Number of Errors5.004.504.00 3.003.503.00 2.382.502.001.50 0.75 0.33 0.25 0.501.00 0.250.500.00 T01 T02 T03 T04 T05 T06 T07 Means of errors for each task (n=10) 9 / 15
  12. 12. Time-on-task Results300250200150100 50 0 T01 T02 T03 T04 T05 T06 T07 Time (seconds) spent on each task (n=10) 10 / 15
  13. 13. Task Completion and Success Rate ID Completion Success T01 10 9 T02 10 9 T03 6 6 T04 10 10 T05 10 9 T06 10 10 T07 7 6 11 / 15
  14. 14. Workload NASA TLX5.004.504.00 3.50 3.503.50 3.003.00 2.502.50 2.002.00 1.501.501.000.500.00 Mental demand Physical demand Temporal demand Frustration Effort Good performance Means of the user workload (n=10) 12/ 15
  15. 15. User Satisfaction Results Lot of learning needed 1.00 Cumbersome 2.00 Inconsistency 2.00 Assistance needed 2.00 Complexity 2.00 Confidence 3.00 Ease of learning 4.00 Integration 4.00 Ease of use 4.00Willingness to use frequently 3.50 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00 Means of user satisfaction (System Usability Scale) (n = 10) 13 / 15
  16. 16. Self-reported metrics on the SUI654 33 22 1 110 Poor recognition (confusion) Voice not recognised Clear utterance (TTS) Turn taking Means of self-reported metrics on the SUI (n=10) 14 / 15
  17. 17. Conclusion and Future work• Mobile SUI can only be useful if there are few usability issues and recognition rate is high.• The SUI of MIMIC was effective in sending text messages and making calls• The user dictation was a source of errors• Future work: – Implementation of the context-aware module – Weather, GPS and sensor information will be used to determine possible distraction level (from 1 to 5) 15 / 15
  18. 18. Thank You Contact:Emails: Patrick.TchankueSielinou@nmmu.ac.za Janet.Wesson@nmmu.ac.za Dieter.Vogts@nmmu.ac.zaPhone Numbers: 041 504 2323, 041 504 2088

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