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Hpai class slides 020619
- 1. CIIC#5995&100#/#ICOM#5995&100 Human#Perspective#in#Artificial#Intelligence# (HPAI) Professor'José'Meléndez,'PhD https://zoom.us/j/612405776 "Music is theuniversal language of mankind." A Henry Wadsworth Longfellow (180771882)
- 2. Previously+in+HPAI+CIIC/ICOM+5995 • The “Environment”is Reality • Only 5 types of Sensible Energies or Interactions. • Our “Representations” of our Observable Environment Create Our Realities • Human senses only detect a very small part of what is sensible of Reality • Some animals can do better…
- 3. Next%Up%– Human%vs.%Artificial%Sensing • Sound&Sensing •How&we&Hear • Frequency&Range • Dynamic&Ranges • Artificial&Hearing • Light&Sensing • Smell&Sensing • Taste&Sensing • Touch&Sensing& • Internal&Sensing
- 4. Human&Ear&– aka&“Mic” • Outer&Ear&collectsvibrating&air to&move&Ear&Drum • Middle&Ear&couples energy&into&vibrating&bones • Inner&Ear&couples energy&into&vibrating&fluid • Vibrating&Cochlea&hairs&transform energy&into&electrical impulses&
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- 15. Next%Up%– Human%vs.%Artificial%Sensing • Sound&Sensing •Dynamic&Ranges • Artificial&Hearing • Light&Sensing • Smell&Sensing • Taste&Sensing • Touch&Sensing& • Internal&Sensing
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- 19. Sound&Range&at&Middle&Frequency http://www.cochlea.org/en/hear/human2auditory2range • Human conversation9takesplace well within the frequency range heard • How low a volume we can hear varies9with9frequency • How9high9a9volume9we9can9hear9also varies with frequency
- 20. Sound&“Volume”&Sensitivities https://dosits.org/science/measurement/what4sounds4can4we4hear/ • What6we6hear6– music6and6voice6–is6tuned6to6how6we6hear6frequencies6and6volume • Our6music6and6conversations6are6not6considerate6of6an6animal’s6optimal6hearing6
- 21. Sound&“Volume”&Sensitivities https://dosits.org/science/measurement/what4sounds4can4we4hear/ • So6elephants6can6better6appreciate6human6music6– shift6frequencies6downward •So we can better understand elephants,6we can shift their6sounds6upwards6
- 22. Sound&“Volume”&Sensitivities https://dosits.org/science/measurement/what4sounds4can4we4hear/ • So6cats6can6better6hear6/6understand6us,6we6should6shift6voice6frequencies6upwards • Sowe can better understand cats,6we can shift animal6sound6frequencies6downwards6
- 23. Next%Up%– Human%vs.%Artificial%Sensing • Sound&Sensing •Artificial&Hearing • Light&Sensing • Smell&Sensing • Taste&Sensing • Touch&Sensing& • Internal&Sensing
- 24. Alexander)Graham)Bell’s)Mic • Upper%Box%collects vibrating%airto%move%Lower%Diaphragm%(“Drum”) • Drum%couples energy%into%attached%vibrating%Pin • Pin%contact%area%with%conducting%fluid%(acid)%changes • Vibrating%energy%transforms into%oscillating%electrical current https://www.antiquetelephonehistory.com/images/firstFliquid.jpg
- 25. • Microphones+transform+vibrations+into+digital+audio+signals • Digital+audio+signals+transmitted+inside+ear+by+radio+frequencies+ •RF+signals+converted+to+electrical+impulses+at+electrode array+in+cochlea Cochlear)Implants,)Blausen.com staff)(2014).)"Medical)gallery)of)Blausen)Medical)2014" Cochlear)Implants
- 26. Sound&Sensors&– “Microphones” Courtesy)of)Vesper • Vibrating)airmoves)Diaphragm • Vibrating)Diaphragm)and) “backplate”)transform energy) into)electrical capacitance)
- 27. Sound&Sensors&– “Microphones” Courtesy)of)Vesper • Vibrating)airmoves)Plates • Plates)couple energy)into) vibrating)Piezoelectric)Film • Vibrating)Piezoelectric)film) transforms energy)into) electrical charge)
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- 30. Human&Sound&Applications of&AI • Voice&Machine&Communications •Audio&Fingerprinting • Audio&Classification&/&Labeling • Voice&to&Text • Audio&Source&Separation • Audio&Search • Music&Transcription • Voice Language Translation • Music&Recommendation SOME EXAMPLES
- 31. Audio&Classification&Example • Audio&Detection&(microphone) • Convert&vibrational&energy&to&analog&electric&signals •Convert analog&electric&signals&to&digital&data • Digitization&and&Storage • Convert digital data to audio file format of choice • Save&data • Access&and&Conditioning • Convert&saved data back&to&digital data • Extract features of&interest&from&the&audio&data • Train AI on the selected features
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- 33. Audio&Classification&Example Audio&Signal&Chain&– Analog&to&Digital&Conversion Resolution =2b where&b=&#&of&bits&(16?24&typical) Sampling Frequency (> typically&2x&maximum content frequency) https://www.analyticsvidhya.com/blog/2017/08/audio?voice?processing?deep?learning/
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- 36. Next%Up • Light&Sensing • Smell&Sensing •Taste&Sensing • Touch&Sensing& • Internal&Sensing