User:Angeliki/Grad-prototyping: Difference between revisions
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1 Η ο At AtDf Fe|Sg|Nm 2 Atr _ _ | 1 Η ο At AtDf Fe|Sg|Nm 2 Atr _ _ | ||
</source> | </source> | ||
=== Radio2text === | |||
I want to use speech_recognition to transcribe speech from radio (FM, AM, FSK,...) | |||
=== Collect radio sounds === | |||
An attempt to collect radio sounds depending on what text accompanies them, on time, on frequencies or other factors. For example every time the software listens to streaming and recognizes a sound of voice (300 and 3000 Hz) or a word then it records down/collects. | |||
== Antennas == | == Antennas == | ||
[[File:Directing to satellites.JPG|500px|Directing to satellites]] | [[File:Directing to satellites.JPG|500px|Directing to satellites]] | ||
[[OuNuPo_Publishing#web_radio|Web Radio]] | [[OuNuPo_Publishing#web_radio|Web Radio]] |
Revision as of 15:04, 1 October 2018
Zine-machines
export GPS data, publish routes/video frames to raw data-publish
import pykml
from pykml import parser
import csv
import re
from reportlab.lib.pagesizes import letter
from reportlab.pdfgen import canvas
def translate(value, leftMin, leftMax, rightMin, rightMax):
# Figure out how 'wide' each range is
leftSpan = leftMax - leftMin
rightSpan = rightMax - rightMin
# Convert the left range into a 0-1 range (float)
valueScaled = float(value - leftMin) / float(leftSpan)
# Convert the 0-1 range into a value in the right range.
return rightMin + (valueScaled * rightSpan)
kml_file='prlll.kml'
all_routes = {}
with open(kml_file) as f:
doc = parser.parse(f).getroot().Document.Folder
for pm in doc.iterchildren():
if hasattr(pm, 'LineString'):
name = pm.name.text
coordinates = pm.LineString.coordinates.text
cordinatesinline = coordinates.split('\n')
cordinatesasarray = []
for line in cordinatesinline:
pattern = re.compile("^\s+|\s*,\s*|\s+$")
array = [x for x in pattern.split(line) if x]
if array:
cordinatesasarray.append(array)
all_routes[name]= cordinatesasarray
canvas=canvas.Canvas("route.pdf", pagesize=letter)
canvas.setLineWidth(.8)
canvas.setFont('Helvetica', 6)
for name in all_routes:
x=[]
y=[]
for points in all_routes[name]:
x.append(points[0])
y.append(points[1])
i=0
for a in x:
if i < len(x)-1:
x_new=translate(float(x[i]),float(min(x)), float(max(x)),50,500)
y_new=translate(float(y[i]),float(min(y)),float(max(y)),50,500)
x_new2=translate(float(x[i+1]),float(min(x)), float(max(x)),50,500)
y_new2=translate(float(y[i+1]),float(min(y)),float(max(y)),50,500)
print x_new,y_new,x_new2,y_new2
canvas.line(x_new,y_new,x_new2,y_new2)
i=i+1
canvas.drawString(10,45,name)
canvas.showPage()
canvas.save()
Walking/annotating/listening/transcribing/present voice
Walking the text
Los Banos(PH) voices/ Nomidu Nuna Exhibition
The secrets of pocketsphinx
Acoustic model/training
0 46797 She had your dark suit in greasy wash water all year.
File:
1 Η ο At AtDf Fe|Sg|Nm 2 Atr _ _
2 Σίφνος Σίφνος No NoPr Fe|Sg|Nm 3 Sb _ _
3 φημίζεται φημίζομαι Vb VbMn Id|Pr|03|Sg|Xx|Ip|Pv|Xx 0 Pred _ _
4 και και Cj CjCo _ 5 AuxY _ _
5 για για AsPp AsPpSp _ 3 AuxP _ _
6 τα ο At AtDf Ne|Pl|Ac 8 Atr _ _
7 καταγάλανα καταγάλανος Aj Aj Ba|Ne|Pl|Ac 8 Atr _ _
8 νερά νερό No NoCm Ne|Pl|Ac 5 Obj _ _
9 των ο At AtDf Fe|Pl|Ge 11 Atr _ _
10 πανέμορφων πανέμορφος Aj Aj Ba|Fe|Pl|Ge 11 Atr _ _
11 ακτών ακτή No NoCm Fe|Pl|Ge 8 Atr _ _
12 της μου Pn PnPo Fe|03|Sg|Ge|Xx 11 Atr _ _
13 . . PUNCT PUNCT _ 0 AuxK _ _
1 Πιστεύω πιστεύω Vb VbMn Id|Pr|01|Sg|Xx|Ip|Av|Xx 0 Pred _ _
2 ότι ότι Cj CjSb _ 1 AuxC _ _
3 είναι είμαι Vb VbMn Id|Pr|03|Sg|Xx|Ip|Pv|Xx 2 Obj _ _
4 δίκαιο δίκαιο No NoCm Ne|Sg|Nm 3 Pnom _ _
5 να να Pt PtSj _ 7 AuxV _ _
6 το εγώ Pn PnPe Ne|03|Sg|Ac|We 7 Obj _ _
7 αναγνωρίσουμε αναγνωρίζω Vb VbMn Id|Xx|01|Pl|Xx|Pe|Av|Xx 3 Sb _ _
8 αυτό αυτός Pn PnDm Ne|03|Sg|Ac|Xx 7 Obj _ _
9 . . PUNCT PUNCT _ 0 AuxK _ _
1 Η ο At AtDf Fe|Sg|Nm 2 Atr _ _
Radio2text
I want to use speech_recognition to transcribe speech from radio (FM, AM, FSK,...)
Collect radio sounds
An attempt to collect radio sounds depending on what text accompanies them, on time, on frequencies or other factors. For example every time the software listens to streaming and recognizes a sound of voice (300 and 3000 Hz) or a word then it records down/collects.