Slides from a keynote talk at the University of Manchester UK Schools Computer Animation Competition in July 2014.
http://animation14.cs.manchester.ac.uk/festival/
27. Feature Extraction
We can analyse a piece of music to ļ¬nd out
what sounds are happening at different
times
!
Low frequencies: e.g.Bass
Mid frequencies: e.g.Vocals
High frequencies: e.g.Cymbals
This gives us a Spectrogram
54. Lossy Encoding
My nm s Sn nd m Cmptr Scntst t th nvrsty f
Mnchstr.
!
lk t ply th gtr.lk t g scb dvng nd shrks r my
fvrt nmls.
111 letters
55. Lossy Encoding
My name is Sean and I'm a Computer
Scientist at the University of Manchester.
!
I like to play the guitar.I like to go scuba
diving and sharks are my favourite
animals.
170 letters
56. Lossy Encoding
Original = 170 letters,New = 111 letters
!
65% smaller!
!
Imagine if we had to pay Ā£1 per letter!
!So this isācheaperā,but we might need
some extra effort to read it
57. Lossy Encoding
ae i ea a I a oue iei a e Uiei o aee.
I ie o a e uia.I ie o o ua ii a a ae aouie aia.
53 letters
58. Lossy Encoding
My name is Sean and I'm a Computer
Scientist at the University of Manchester.
!
I like to play the guitar.I like to go scuba
diving and sharks are my favourite
animals.
170 letters
62. How high?
1.Everybody stand up!
2.You will hear a tone play.
3.When you can no longer hear
the tone,sit down!
Thisisanexperiment,notacompetitionāno
cheating!
103. Computer Science isn't just about
Computers
We can't predict what the impact of
new technologies will be
Sharks are great!
Eat lots of broccoli!
Things to Remember