Developing with Alexa

1. CW
IN
CAPGEMINI
WEEK OF
INNOVATION
NETWORKS
Developing with Alexa
Sarah Saunders OSCE

2. Presentation Title | Author | Date © 2018 Capgemini. All rights reserved. 2
Building an Alexa Skill
• Why?
• What does it do?
• How does it work?
Demo…
Application Walk-through
Conclusions and Opinions on
Alexa Development
Agenda

3. Presentation Title | Author | Date © 2018 Capgemini. All rights reserved. 3
Building an Alexa Skill
• Why?
• What does it do?
• How does it work?
Demo…
Application Walk-through
Conclusions and Opinions on
Alexa Development
Agenda

4. Presentation Title | Author | Date © 2018 Capgemini. All rights reserved. 4
Platinum Sponsor - recruitment
and promotion
Theme: “It takes all types to
make a team”
Techy demos, talking points,
catch peoples’ attention and
interest
Fun as a core value
Why: Capgemini at Devoxx UK

5. Presentation Title | Author | Date © 2018 Capgemini. All rights reserved. 5
Community version of Myers Briggs personality test
32 questions, in the format “Do you prefer A or B”, where A
and B are opposites
Each must be answered on a scale of 1 to 5
An algorithm allocates you one of 16 personality types,
comprising of a combination of four “base” personality type
pairs (see below), based on your answers
Questions are open source; modified by the psychology
community
How to convert someone’s vocal answer into a 1 to 5 scale
How to get Alexa to recognise your answers (more on that
later)
Convert the OEJTS answer to a technology “type”
Shorten the questionnaire to make it completable
Fun, not opinionated
Don’t offend anybody! (FAIL)
Questionnaire Challenges
What: Open Extended Jungian Type Scales
Personality Types
Introverted / Extroverted (I / E)
Sensing / iNtuiting (S / N)
Feeling / Thinking (F / T)
Perceiving / Judging (P / J)
} 16 combinations (e.g.) INTJ, ENTJ…

6. Presentation Title | Author | Date © 2018 Capgemini. All rights reserved. 6
Software Engineering “Personality Types”
Server
Side
Dev
Front
End
Dev
DevOps
New
Tech
Agile
Coach
ESFP,
ISFP,
ENFP
ESTJ,
ENTJ,
ESFJ,
ISFJ
ENFJ,
INFJ,
INFP
ISTJ,
INTJ,
INTP,
ISTP
ESTP,
ENTP

7. Presentation Title | Author | Date © 2018 Capgemini. All rights reserved. 7
#DiversiTeams 

8. CW
IN
CAPGEMINI
WEEK OF
INNOVATION
NETWORKS
Demo

9. Presentation Title | Author | Date © 2018 Capgemini. All rights reserved. 9Presentation Title | Author | Date © 2018 Capgemini. All rights reserved.
Alexa Voice Services (AVS) Lambda FunctionInvocation Model - ASK
Security
Client APIs (Echo, Java..) include:
• Wake Word logic
• When to start and stop recording
• Create sound file and send to
Amazon server
Server API:
• Converts sound to text
• Triggers Invocation Model
How: Alexa Skill Components
Browser based IDE
JSON file
Slots
Types – MANY predefined types (inc.
Names, Places…!)
Define every possible recognizable
answer to your questions
Passes slot values to server – lambda
or other
Event-driven
Javascript (or Java, Python, C#)
Contains states to manage flow
Use APIs to hook in other logic (ie
sentiment analysis)
Available “Skills” are linked via your AWS account
Client API uses OAuth to authenticate with your AWS account – you grant it permission to access the skills in your account
Token based authentication between invocation model of skill and server-side logic (ie lambda function)

10. Presentation Title | Author | Date © 2018 Capgemini. All rights reserved. 10
Interaction Model Drill-down - Types
{“interactionModel”:{
"languageModel": {
"invocationName":"analyse me“,
"types": [
{
"name": “QUIZ_ANSWER",
"values": [
{
"name": {
"value": "make lists",
"synonyms": []
}
},
"name": {
"value": "rely on memory",
"synonyms": []
}
} ………………………… and on and on

11. Presentation Title | Author | Date © 2018 Capgemini. All rights reserved. 11
Interaction Model Drill-down - Intents
{“interactionModel”:{
"languageModel": {
…
"intents": [
{
"name": "AMAZON.CancelIntent",
"samples": []
},
"name": “AnswerIntent",
"slots" : [
"name" : "QuizAnswer",
"type" : "QUIZ_ANSWER"
]
"samples": [
“{QuizAnswer}”
“I {QuizAnswer}”,
“Probably {QuizAnswer}”
……
]

12. Presentation Title | Author | Date © 2018 Capgemini. All rights reserved. 12
Interaction Model Drill-down – Custom Types in Intents
{
“name”: “AskNameIntent”,
“samples”:[
“{sarah|Name}”,
“It’s {sarah|Name}”,
“My name is {sarah|Name}”,
“I’m {sarah|Name}”
],
“slots”:[
{
“name”: “Name”,
“type”:”AMAZON.LITERAL”
}
]
}

13. Presentation Title | Author | Date © 2018 Capgemini. All rights reserved. 13
Server Side Drill Down – States
const states = {
START: "_START",
QUIZ: "_QUIZ",
ASSERT: "_ASSERT"
};

14. Presentation Title | Author | Date © 2018 Capgemini. All rights reserved. 14
Server Side Drill Down – States
const startHandlers = Alexa.CreateStateHandler(states.START,{
"Start": function() {
this.response.speak(WELCOME_MESSAGE).listen(HELP_MESSAGE);
this.emit(":responseReady");
},
"QuizIntent": function() {
console.log("QuizIntent Intent");
this.handler.state = states.QUIZ;
this.emitWithState("Quiz");
}
});
const quizHandlers = Alexa.CreateStateHandler(states.QUIZ, {
"Quiz": function() {
this.emitWithState("AskQuestion");
},
"AskQuestion": function() {
this.emit(":ask", questions[counter]);,
},
"HelpIntent": function() {
// message specific to answering psychometric query
},
"AnswerIntent": function() {
var answer = getSlot(this.event.request.intent.slots); // This would be the answer to the above question
.....
this.handler.state = states.ASSERT;
this.emit(":ask", "Are you sure?");
});
const assertHandlers = Alexa.CreateStateHandler(states.ASSERT, {
"HelpIntent": function() {
// message specific to answering the are-you-sure query
},
"AnswerIntent" : function() {
var answer = getSlot(this.event.request.intent.slots); // This would be the response to the "are you sure?" question
....
this.handler.state = states.QUIZ; // ready for the next question

15. Presentation Title | Author | Date © 2018 Capgemini. All rights reserved. 15
OEJTS questions require an answer between 1 and 5
How do we turn the user’s response into a number?
• Capture the answer to each question. If the first answer is
selected, weight as 2. If the second answer is selected,
weight as 4.
• For each question, have a follow-up question along the
lines of “are you sure”?
• Run the response to this second question through
sentiment analysis to determine if positive or negative.
• If positive, add 1 to first answer or subtract 1 from second
answer (So, 2 becomes 1, 4 becomes 5)
• If negative, subtract 1 from first answer or add 1 to
second answer (So, 2 becomes 3 and 4 becomes 3)
• If neutral, leave as-is
Provide a sentence, receive a positivity scale 0 (negative) to
1 (positive)
Text based – any vocal sentiment (sarcasm, pitch, volume,
tone) is lost
How does it work internally?
• Neural network?
Is this more accurate than 1 to 5?
Problem: Input to Alexa is one sentence Sentiment REST API – theysay.io
Add in some AI – Sentiment Analysis

16. Presentation Title | Author | Date © 2018 Capgemini. All rights reserved. 16Presentation Title | Author | Date © 2018 Capgemini. All rights reserved.
01
02
03
Lessons
Learned When to use Voice Interfaces
 Slow - slower than reading or typing or touch screen
interaction
 No need to use your hands – can multi task
 Small input/output
 Alexa / Siri / Google / Cortana are all quite different
Voice Interface Development Skills
 Understanding of Conversation structure
 Language and Culture Specific
 Do not create open-ended questions!
 Use of Random to give a realistic feel
Golden Rules of IoT
 Address Security First – Alexa a good platform for this
 Always have a manual override!
 Be aware of GDPR

17. Presentation Title | Author | Date © 2018 Capgemini. All rights reserved. 17
Voice interfaces are suitably
advanced that they should
always be considered an option
Alexa skills are curiously limited
Click to insert text
People loved the OETJS –
analyzing themselves, the
human angle
sarah.saunders@capgemini.com
@sasaunde
Questions / Comments?
Conclusions