the birth of doraemon
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TAIPEI | SEP. 21-22, 2016
Hao Wu, Cheng Hsin Lee 2016/09/21
THE BIRTH OF DORAEMON
2
AGENDA
Whats a Robot
The birth of DoraemonFunctions and Application scenarios
Difficulties and ChallengesAI2 for Service Robot
3
ABOUT US
Tide Technology (Beijing) Ltd.
2014.4 2015.7 2016.9
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WHATS A ROBOT
5
WHATS A ROBOT
Perception Thinking Decision-making Implementation
Robot is made of a complex system
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WHY DO DORAEMON
All of us have a dream in childhood,to have one Doraemon.
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THE BIRTH OF DORAEMON
R&D for over 1 year,10+ professional teams close cooperation,more than 200 engineers effort,6 times optimizing on prototypes!
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THE FUNCTION OF DORAEMON
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APPLICATION PERSPECTIVE
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PRESENTATIONListen to reading in familiar voice
Solutionto acquire users Voice Model through deep learning method
PracticeReading for 23 minutes36 sentences
Application scenariosReading news for elder in Childrens voice
Reading story for child in Mothers voice
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PRESENTATIONEmotion Recognition
To analyze emotion via face recognition.
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DIFFICULTIES AND CHALLENGES
Tegra TX1
AI2 FOR SERVICE ROBOTAI2 = AI Application & Integration
Resources1. Algorithm2. Data3. Calculation capability
Machine Learning1.Unsupervised2.Supervised3.Reinforcement learning
AI2 + Robot1.EnvironmentPerceive2.PeopleUnderstand&Communication3.Autonomous Learning
1.Visual Perception & Understanding
(Supervised Deep Learning)
2.Strategic Dialogue System
(Deep Reinforcement Learning)
PROJECTS
1. Training Env.
2. Run time Env.
HARDWARE
OS Ubuntu 14.04
CUDA Nvidia
Performance Libarary - Nvidia
for Visual Perception : Framework Torch (facebook open source), Neural Talk
For Strategic Dialogue System : Framework ConvNet, SimpleDS
Dataset : Microsoft COCO & ImageNet
SOFTWARE
Global Opened Dataset Global Opened Model : VGGNet
PROJECT : DATASET & MODEL
CNN
object recognition
RNN
language model
PROJECT : ARCHITECTURE
Smart home environment
PROJECT : TRANSFER OF LEARNING
PROJECT : FINDING
PROJECT : APPROACHDeep Reinforcement Learning
PROJECT
Strategic DialogueDeep Reinforcement
LearningStrategic Dialog System
For compliance
REFERENCE
CVPR 2015 Paper Deep Visual-Semantic Alignments for Generating Image Descriptions Andrej Karpathy, Li Fei-Fei http://www.cs.toronto.edu/~frossard/post/vgg16/ H. Cuayhuitl. SimpleDS: A Simple Deep Reinforcement Learning Dialogue System. International
Workshop on Spoken Dialogue Systems (IWSDS), 2016 https://www.cs.utexas.edu/~eladlieb/RLRG.html
TAIPEI | SEP. 21-22, 2016
Thank you