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Hello humans !
Forget everything !
Everything you know…
Everything you learned…
is OVER !!!
Welcome to a brand new world…
The world of VOICE
From Alexa
To Google Home,
In-car systems,
and smartwatches
Touch is no longer the primary UI
The touch era is OVER !
Chatbot and Conversational
Experiences with Amazon
Alexa, Neo4j and
GraphAware NLP
GraphDB Meetup Czech Republic
June 14th, 2017
Christophe Willemsen - @ikwattro
Program of tonight
• Chatbots history
• Voice-driven chatbot anatomy
• Let’s build our conference assistant
• Introduction to Natural Language Processing
• Let’s chat..bot
Chatbots history
• Alan Turing Test
Chatbots history
• Eliza (1966) mimicked human conversations by matching user
prompts to scripted responses. It was able, at least for a time, to
pass the Turing test
Chatbots history
• Parry (1972) – Inexplicably simulated a person with paranoid
schyzophrenia. Parry was more advanced than Eliza.
Chatbots history
• 1988 – Jabberwacky
• 1992 - Dr. Sbaitso
• 1995 – A.L.I.C.E
• 2001 – Smarterchild
• 2006 – IBM’s Watson
• 2010 – SIRI
• 2012 – Google NOW
• 2016 – Bots for Messenger, TAY
• And Alexa ? Ask her !
Chatbot anatomy
• Voice Commands
• Intent detection
• Intent handling
• Response
Our conference assistant
• Tell me how many sessions ?
• Tell me how many sessions about a specific topic ?
• Recommend me a session based on my topic preferences
• Find me a session about a specific topic with NLP
Alexa should be able to :
Dataset used
Graphconnect London 2017 schedule
Voice command
• Give a name to our Alexa skill -> CONFERENCE ASSISTANT
• Define our first intent name (code) -> talksCount
• Define our first utterance
ALEXA, ASK CONFERENCE ASSISTANT
(skill invocation)
HOW MANY SESSIONS TODAY ?
(skill utterance)
INTENT DETECTION
SPEECH TO TEXT
TEXT TO SPEECH
LAMBDA FUNCTION
OR
YOUR API SERVER
ALEXA VOICE SERVICE
Utterances
• How many sessions ?
• How much sessions ?
• How many talks at the conference ?
• How many talks today ?
Intent detection
• 2 main types of detection :
-> Pattern matching (how | count)* many (session | talks) today?
-> Classification machine learning, neural networks, word2vec, ..
Alexa send to the skill API
Your skill returns a text response
Intent detection
• 2 main types of detection :
-> Pattern matching (how | count)* many (session | talks) today?
-> Classification machine learning, neural networks, word2vec, ..
First intent test
ALEXA, HOW MANY SESSIONS TODAY ?
ALEXA, ASK CONFERENCE ASSISTANT
(skill invocation)
HOW MANY SESSIONS TODAY ?
(skill utterance)
INTENT DETECTION
SPEECH TO TEXT
TEXT TO SPEECH
LAMBDA FUNCTION
OR
YOUR API SERVER
ALEXA VOICE SERVICE
Slots
• Variables in the utterances
• Should be filled with possible values
• Slots are sent in the intent request to your API
Slots
HOW MANY SESSIONS ABOUT {topic}
Second intent test
ALEXA, HOW MANY SESSIONS ABOUT
PERFORMANCE ?
Adding personalization
• If you have informations about the attendees and their topic
preferences, you can easily get the sessions in accordance with it.
Adding personalization
Adding personalization
Third intent test
ALEXA, RECOMMEND ME A SESSION
GraphAware NLP
• Graph based Natural Language Processing framework
• Information Extraction, Sentiment Analysis, Data enrichment
(ontologies and concepts), similiraty computation, knowledge
enrichment, …
• Beta program, first public open-source version to be released very
soon
Enriching with concepts
Enriching with concepts
Tackling the last intent
• Question / response game
• Treat question as text and process NLP
• Relate question text with Session abstracts texts
• Special type of utterance with only one slot {text}
Demo
Fun / Ideas with Alexa
Resources
• https://github.com/alexylem/jarvis
Thank you !
Questions?
graphaware.com
@graph_aware

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