Machine learning (ML) can help people with disabilities by using facial and object recognition, text-to-speech, automatic translation, and transcription to create assistive applications. In this chalk talk, learn how to assemble ML APIs from AWS to help people in new ways.

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Improve Accessibility Using
Machine Learning
Troy Larson
Senior Cloud Architect
AWS
A I M 3 3 2
Robin Dautricourt
Principal Product Manager
AWS

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Accessibility
Using technology to make every experience in
the world accessible to people with disabilities

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Machine learning
Method of data analysis that automates
analytical model building
Machines learn from data, identify
patterns, and make intelligent decisions
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20+ years of machine learning at Amazon
Drones Voice-driven interactions Reinventing customer
experience
Personalized
recommendations
Fulfillment automation Inventory management

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Frameworks &
Infrastructure
AWS Deep Learning AMI
GPU
(P3 Instances)
MobileCPU
IoT
(AWS Greengrass)
Vision:
Amazon Rekognition Image
Amazon Rekognition Video
Speech:
Amazon Polly
Amazon Transcribe
Language:
Amazon Lex
Amazon Translate
Amazon Comprehend
Apache MXNet
on AWS PyTorch
Cognitive
Toolkit
Keras
Caffe2
& Caffe
TensorFlow Gluon
Application
Services
Amazon ML
Services
Amazon
SageMaker
AWS
DeepLens
Amazon Machine Learning (Amazon ML) stack

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Common language use cases
Information bots
Education
Accessibility
Knowledge managementVoice of customer
applications
Customer service/
call centers
Enterprise
digital assistant
Semantic search
Captioning workflows
LocalizationPersonalization

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Cognixion
Use Amazon Polly to allow
people with communication
challenges to engage in
conversation
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Echo360
Use Amazon Transcribe to analyze video and
presentations for closed-captioning and content
engagement

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Example 3 (TBD)Pollexy

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12. Thank you!
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Troy Larson
troylars@amazon.com
Robin Dautricourt
rdautric@amazon.com

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