The document highlights Microsoft's AI portfolio, including services like Cortana and Azure Machine Learning, aimed at enhancing customer service through cognitive capabilities. It discusses the challenges and costs involved in implementing language understanding systems, while also presenting features to create and maintain personalized models easily. Additionally, it lists upcoming sessions for further learning about integrating these technologies into applications.

4. Agent Applications Services Infrastructure
Microsoft AI Portfolio
Cortana Office 365
Dynamics 365
SwiftKey
Pix
Customer Service
and Support
Bot Framework
Cognitive Services
Cortana Intelligence
Cognitive Toolkit
Azure Machine
Learning
Azure N Series
FPGA
People

5. Microsoft
Cognitive
Services
Give your apps
a human side

6. Cet outil de traduction est
un moyen facile d'étendre
la portée de vos contenus
internes et externes.
Client app or webpage
此翻译工具是可以轻松
地扩展您的内部和外部
内容的覆盖范围。
WEB API

7. =‫لغة‬‫البيانات‬
語言資料
данные языка
भाषा डेटा
language data
données linguistiques

8. s all about context
VS
consectetur
Lorem ipsum
sit amet
Maecenas mattis justo
eros, a consequat
ante tristique at.
Word

9. https://translator.microsoft.com/neural

10. Human Automatic
Quality Best Mediocre to good
Scalability Limited Limitless
Turnaround Time Hours to Days Second(s) to Minutes
Cost 12cts per word 1/20,000th of 12cts/word

11. Microsoft Confidential
•
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•
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•
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•
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Client app
Translated text
WEB API

13. Speech Recognition
TrueText
Speech Correction
Translation
Text to Speech
um no i mean yes but i am i've never done
it myself did users before uh I will ask go
deep to help me
Yes.
But I’ve never done it myself.
Did you use yours before?
I will ask Gurdeep to help me.
um no i mean yes but i am i've never done
it myself did you use yours before uh I will
ask gurdeep to help me
no i mean yes but I am i've never done it
myself did you use yours before uh I will
ask gurdeep to help me
Raw ASR Output
Lattice Rescoring
Disfluency Removal
Segmentation
Punctuation and
True Casing
Oui.
Mais je ne l'ai jamais fait moi-même.
Avez-vous utilisé le vôtre avant?
Je vais demander à Gurdeep de m'aider
um non je veux dire oui, mais je suis je n'ai
jamais fait moi-même les utilisateurs avant e
UH .je vais demander aller profondément
pour m'aider
`
Same translation
system, major
output difference

15. Partial Transcripts
Final Transcripts
Partial Translations
Final Translations

16. 
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 http://translate.it http://translator.microsoft.com


19. • Great to meet you !
• I need to extend my booking next week by one day .
• Can you also book me a car ?
“Great to meet you ! I need to extend my booking next week
by one day. Can you also book me a car?”

24. Word Breaks Slang
HomonymsNames
Brands

25. {
"offset": 48,
"token": "grate",
"type": "UnknownToken",
"suggestions": [
{
"suggestion": "great",
"score": "0.949079025281377"
}]
}
{
"offset": 23,
"token": "Seattle. hope",
"type": "UnknownToken",
"suggestions": [
{
"suggestion": "Seattle. Hope",
"score": "0.875"
}]
}
Hello Build! Welcome to Seattle. hope you have a grate week

26. { "query":
"tell me a jke",
"topScoringIntent": {
"intent": "Joke",
"score": 0.45167464 }
{ "query":
"tell me a jke",
"alteredQuery":
"tell me a joke",
"topScoringIntent": {
"intent": "Joke",
"score": 0.99875766 }

27. Language understanding in human-computer interaction is:
Technically
challenging
It’s exceedingly difficult to enable a
computer to understand what a
person wants and to find the pieces
of information that are relevant to
their intent.
Costly
to implement
Building and maintaining machine
learning systems requires a large
investment of time, money and
engineering resources
Often
domain specific
In the past, building your own
machine learned models often
required assistance of a team of
data scientists that would customize
the models to the specific domain.

28. L A N G U A G E U N D E R S T A N D I N G
Create your
own LU model
Train by providing
examples
Deploy to an HTTP
endpoint and
activate on any
device
Maintain model
with ease

30. (*) Recognizers are open-sourced.
More New Features
L A N G U A G E U N D E R S T A N D I N G
Top Requested Features
Production Staging and Versioning
Sharing
More Languages (Dutch, Korean, dialects)
Documentation
Increased Intent (80) and Entity Limits (30)
25 Customizable Prebuilt Domains
New Dashboard
Testing
Lists
Improved Recognizers(*)
Semantic Dictionaries
Spell Checking

34. {
"text": "I want a Surface Laptop",
"intent": "BuyProduct",
"entities":
[
{
"entity": "Product",
"startPos": 10,
"endPos": 26
}
]
}

36. Age Dimension Email
Encyclopedia Geography Money
Number Ordinal Percentage
Phonenumber
(US)
Temperature Url

37. https://github.com/Microsoft/Recognizers-Text

42. Microsoft
Cognitive
Services
Give your apps
a human side

43. https://www.microsoft.com/cognitive-services
https://docs.microsoft.com/en-us/azure/cognitive-services/
Channel 9
Microsoft Virtual Academy

44. #MSBuild
Re-visit Build session recordings on Channel 9
Session ID Title Day/Time Location
B8071 Navigating the AI Revolution 5/10 11:30 AM TCC L3 Tahoma 3 (639)
B8092 Using Microsoft Cognitive Services to bring the
power of speech recognition to your apps
5/10 05:00 PM WSCC Room 612 (359)

45. 45