Slide 1Hello!Intelli-what?What is this class about?Why intelligent systems?Examples of intelligent systemsExamples of intelligent systemsExamples of intelligent systemsExamples of intelligent systemsExamples of intelligent systemsExamples of intelligent systemsExamples of intelligent systemsExamples of intelligent systemsCase study: Intelligent audioMaking sense of soundThings we can doVideo Content AnalysisTraffic MonitoringSecurity SurveillanceMore things to doIntelligent audio editingUser-guided sound selectionAudio/visual object editingMany more applicationsSo what does intelligence require?Tools we will useThe bit of mathThe bit of AIDomain-specific AICodingClass goalsProjects to tryThe rulesThe good (or bad!) newsQuestions?Building Intelligent SystemsCS498Hello!•Instructors:–David Forsyth – [email protected]–Paris Smaragdis – [email protected]–Prof. X•And you are …Intelli-what?•What is an intelligent system?–Any takers?What is this class about?•How do we construct intelligent systems?–Note the emphasis!Why intelligent systems?•What’s special about intelligent systems?–Why bother with this class?Examples of intelligent systemsExamples of intelligent systemsExamples of intelligent systemsExamples of intelligent systemsExamples of intelligent systemsExamples of intelligent systemsExamples of intelligent systemsExamples of intelligent systemsCase study: Intelligent audio•“Machine Listening”–Making machines that understand soundMaking sense of sound3.5 4 4.5 5 5.5 6x 104−0.15−0.1−0.0500.050.10.15Huh?Things we can do•Audio classifiers•Train in example sounds–“Teach” a computer•Use to detect learned sounds–Many applicationsVideo Content Analysis•Audio is a strong cue for detecting various events in video•Classify sounds to perform semantic analysis on video–Specific subclasses for type of broadcast (e.g. for news we use male and female speech, for sports use cheering, etc)•Build in high-end Mitsubishi PVRs, TV sets and “HDTV cell phones”Was there a goal?Sad or funny clip?Real-time movie sound parsingTraffic MonitoringNormal crash Hard-to-see crashNear crash Notable (?) eventDetect incidents by recognizing soundsSecurity Surveillance•Detect sounds in elevators–Normal speech, excited speech, footsteps, thumps, door open/close, screams•When detecting suspicious sounds we can raise an alert–96% accuracy in elevator test recordings with actorsElevators are a dark environment with poor visual analysis prospectsAudio analysis can provide optimal detection of distress soundsMore things to do•Make systems that resolve mixtures and figure out objects in a recordingWhat’s in here??Intelligent audio editing2121Piano + SopranoSoprano layerPiano layerRemixed layersOriginal drum loopExtracted layersRemixerRemixerNo tambourineNo congasCongas!Selective pitch shiftingMusic layerVoice layerUser-guided sound selectionAudio/visual object editingInput sequencesOutput sequencesMany more applications•Intelligent audio editing•City grid state–Dublin City Traffic Authority–Cambridge, MA (more later)•Machine Monitoring–Mitsubishi Heavy Industries–Automotive monitors•Building-wide sensor networks•Home security surveillance•Smart phone sensing•Medical listening/surveilance (heart, lungs, speech, ICU)•…So what does intelligence require?•An ability to translate our thoughts to a programming formula–Much harder than it sounds•Let me demonstrate …•But it is also simpler than it sounds!Tools we will use•A bit of math•A bit of artificial intelligence (AI)•Plenty of codingThe bit of math•Some linear algebra•Some probability•Some optimization•Used as needed, we’ll skip the fluf–Don’t be scared!The bit of AI•Machine learning–Making classifiers–Clustering data–Making sense of huge data setsDomain-specific AI•Natural language processing•Computer vision•Speech and audio recognition•…Coding•Plenty of projects–We want this to be a hands-on class•You are free to pick your poison hereClass goals•Overall understanding of the problems in AI-ish areas–*Know how to classify data–*Know how to cluster data•Understand how to represent text, audio, images, video data•Understand probabilistic reasoning•Have basic understanding of the following processes:–How Google works–*How collaborative filtering works (e.g. Netflix, dating sites, etc)–*How face detection or character recognition works–*How speech recognition works–*How text mining works (e.g. language detection, document clustering, sentiment analysis)Projects to try•Automatically organize your PDF/source code collections•Automatically organize your video/music collection•Find faces in pictures or movies•Make an automated call center•Find cliques of friends from social graphs•Make a dating site•Predict NFL/NBA/MLB outcomes•Track a finger on a touch interface•Categorize physiological data, predict user emotions•Categorize network traffic or OS activity•…The rules•We want you to learn, not sufer!•Please engage, don’t just sit back•Grades are determined through the MPsThe good (or bad!) news•This is the first iteration of this class•Tell us what you want to learn!–What’s your domain of interest?–What amazing task do you want to do?Questions?•Email
View Full Document
Unlocking...