Update calcSpeakingTypes()

sonogram_utility.py

@@ -8,6 +8,7 @@ import torch
 import torchaudio
 import pandas as pd
 import datetime as dt
+from sonogram import Sonogram
 
 def colors(n):
   '''
@@ -405,87 +406,19 @@ def calcCategories(myAnnotation,categories):
         cleanCategories.append(newCategory)
     return cleanCategories,extraCategories
 
-def calcSpeakingTypes(myAnnotation,maxTime):
-    noVoice = [Segment(0,maxTime)]
-    oneVoice = []
-    multiVoice = []
-    for speaker in myAnnotation.labels():
-        timesToProcess = []
-        for timeSegment in myAnnotation.subset([speaker]).itersegments():
-            timesToProcess.append((speaker,timeSegment))
-        while len(timesToProcess) > 0:
-            currID, currSegment = timesToProcess[0]
-            timesToProcess.remove(timesToProcess[0])
-            resetCheck = False
-            # Check in multi
-            for compareID,timeSegment in multiVoice:
-                overlapTime = checkForOverlap(currSegment,timeSegment)
-                if overlapTime is None:
-                    continue
-                else:
-                    compareID.append(currID)
-                    newTimes = removeOverlap(currSegment,timeSegment)
-                    for i in range(len(newTimes)):
-                        newTimes[i] = (currID,newTimes[i])
-                    timesToProcess += newTimes
-                    resetCheck = True
-                    break
-            if resetCheck:
-                continue
-            # Check in one voice
-            for timeSlot in oneVoice:
-                tID = timeSlot[0]
-                tSegment = timeSlot[1]
-                overlapTime = checkForOverlap(currSegment,tSegment)
-                if overlapTime is None:
-                    continue
-                else:
-                    oneVoice.remove(timeSlot)
-                    # Add back non overlap
-                    newTimes = removeOverlap(tSegment,currSegment)
-                    for i in range(len(newTimes)):
-                        newTimes[i] = (tID,newTimes[i])
-                    oneVoice += newTimes
-                    # Add overlap time to multivoice
-                    multiVoice.append(([tID,currID],overlapTime))
-                    # Add new times back to process
-                    newTimes = removeOverlap(currSegment,tSegment)
-                    for i in range(len(newTimes)):
-                        newTimes[i] = (currID,newTimes[i])
-                    timesToProcess += newTimes
-                    resetCheck = True
-                    break
-            if resetCheck:
-                continue
-            # Add to one voice
-            oneVoice.append((currID,currSegment))
+def calcSpeakingTypes(pipeline,myAnnotation,maxTime):
+    nvAnnotation = Annotation()
     ovAnnotation = Annotation()
     mvAnnotation = Annotation()
-    for currID,timeSlot in multiVoice:
-        currIDString = '+'.join(currID)
-        mvAnnotation[timeSlot] = currIDString
-        copyOfNo = copy.deepcopy(noVoice)
-        for emptySlot in noVoice:
-            if checkForOverlap(timeSlot,emptySlot) is None:
-                continue
-            else:
-                copyOfNo.remove(emptySlot)
-                copyOfNo += removeOverlap(emptySlot,timeSlot)
-        noVoice = copyOfNo
-    for currID,timeSlot in oneVoice:
-        ovAnnotation[timeSlot] = currID
-        copyOfNo = copy.deepcopy(noVoice)
-        for emptySlot in noVoice:
-            if checkForOverlap(timeSlot,emptySlot) is None:
-                continue
-            else:
-                copyOfNo.remove(emptySlot)
-                copyOfNo += removeOverlap(emptySlot,timeSlot)
-        noVoice = copyOfNo
-    nvAnnotation = Annotation()
-    for emptySlot in noVoice:
-        nvAnnotation[emptySlot] = "None"
     
+    categorySegmentList, timeSteps = pipeline.annotationToNoiseList(myAnnotation)
+    # [group,individual,silence], each as (start,duration)
+    for seg in categorySegmentList[0]:
+        mvAnnotation[Segment(seg[0],seg[0]+seg[1])] = 'group'
+    for seg in categorySegmentList[1]:
+        ovAnnotation[Segment(seg[0],seg[0]+seg[1])] = 'individual'
+    for seg in categorySegmentList[2]:
+        nvAnnotation[Segment(seg[0],seg[0]+seg[1])] = 'silence'
     return nvAnnotation, ovAnnotation, mvAnnotation
 
 def timeToString(timeInSeconds):