Merge branch 'master' of https://git-lium.univ-lemans.fr/Meignier/s4d

.gitignore

@@ -3,4 +3,4 @@ s4d.egg-info/
 */__pycache__/
 *.pyc
 dist/
-
+tutorials/

s4d/diar_tools.py

@@ -221,9 +221,10 @@ def automatonAssignment(diarHyp,diarRef,diarUem=None,tolerance=0,diarFinal__clus
 ## tolerance: In centiseconds
 ## diarFinal__clusterToDeleteAccordingToDiarRef: List of clusters to delete in the diarFinal only
 ## modeNoGap: Drops or not the segment actions (i.e. createSegment & deleteSegment)
-## mergeStrat_BiggestCluster: Whether we merge in the temporal order or first the biggest cluster for a given reference segment
-def automatonSegmentation(diarHyp,diarRef,diarUem=None,tolerance=0,modeNoGap=False,mergeStrat_BiggestCluster=False,diarFinal__clusterToDeleteAccordingToDiarRef=list()):
-    assert isinstance(diarHyp,Diar) and isinstance(diarRef,Diar) and isinstance(mergeStrat_BiggestCluster,bool) and isinstance(modeNoGap,bool) and (diarUem is None or isinstance(diarUem,Diar)) and isinstance(tolerance,numbers.Number) and isinstance(diarFinal__clusterToDeleteAccordingToDiarRef,list)
+## modeNoGap__mergeStrat_BiggestCluster: Whether we merge in the temporal order or first the biggest cluster for a given reference segment (only useful when the modeNoGap is False)
+## deleteBoundarySameConsecutiveSpk: Whether we delete a boundary for two consecutive segments with the same speaker
+def automatonSegmentation(diarHyp,diarRef,diarUem=None,tolerance=0,modeNoGap=False,modeNoGap__mergeStrat_BiggestCluster=False,diarFinal__clusterToDeleteAccordingToDiarRef=list(),deleteBoundarySameConsecutiveSpk=False):
+    assert isinstance(diarHyp,Diar) and isinstance(diarRef,Diar) and isinstance(modeNoGap__mergeStrat_BiggestCluster,bool) and isinstance(modeNoGap,bool) and (diarUem is None or isinstance(diarUem,Diar)) and isinstance(tolerance,numbers.Number) and isinstance(diarFinal__clusterToDeleteAccordingToDiarRef,list) and isinstance(deleteBoundarySameConsecutiveSpk,bool)
     for u in diarFinal__clusterToDeleteAccordingToDiarRef:
         assert isinstance(u,str)
 
@@ -288,7 +289,10 @@ def automatonSegmentation(diarHyp,diarRef,diarUem=None,tolerance=0,modeNoGap=Fal
     showname=diarRef.unique('show')[0]
     diarRef.sort()
     diarHyp.sort()
-    tolerance=abs(tolerance)     
+    tolerance=abs(tolerance)
+    if not strictBoundary:
+        diarRef.pack()
+        diarHyp.pack()     
 
     assert len(diarOverlapArea(diarRef))==0, "Error: diarRef parameter have some overlapped segments.\nReason: No overlap segment allowed.\nSolution: Please put them apart.\n"
     assert len(diarOverlapArea(diarHyp))==0, "Error: diarHyp parameter have some overlapped segments.\nReason: No overlap segment allowed.\nSolution: Please put them apart.\n"
@@ -527,7 +531,7 @@ def automatonSegmentation(diarHyp,diarRef,diarUem=None,tolerance=0,modeNoGap=Fal
                                 valueBoundaryStart=copy.deepcopy(y['stop'])
                     if valueBoundaryStart is None:
                         valueBoundaryStart=valueRef['start']                    
-                    if mergeStrat_BiggestCluster == True:
+                    if modeNoGap__mergeStrat_BiggestCluster == True:
                         # Gets the cluster (it which has the most present frames)
                         dictHypRefSegmentDuration=dict()
                         for y in listHypRefSegment:
@@ -542,10 +546,10 @@ def automatonSegmentation(diarHyp,diarRef,diarUem=None,tolerance=0,modeNoGap=Fal
                             if cls['start']>y['start']:
                                 cls=y
                         clusterName=cls['cluster']
+                    # Moves the boundaries
+                    # Pre-string for a good running: listHypRefSegment sorted in ascending order on start, don't overtake the value valueRef['stop'] and valueRef['start']
                     if modeNoGap == False:            
                         for idx,z in enumerate(listHypRefSegment): 
-                            # Moves the boundaries
-                            # Pre-string for a good running: listHypRefSegment sorted in ascending order on start, don't overtake the value valueRef['stop'] and valueRef['start']
                             nearStop=valueRef['stop']
                             if idx==0:
                                 boundStop=z['stop']
@@ -592,22 +596,21 @@ def automatonSegmentation(diarHyp,diarRef,diarUem=None,tolerance=0,modeNoGap=Fal
                             elif tolerance!=0 and y['start']>=(valueRef['start']-tolerance):
                                 listHypRefSegment.append(y)
                     # Replaces the segments which are not in the correct cluster
-                    replaced=False
-                    for y in listHypRefSegment:
-                        if y['cluster']!=clusterName:
-                            replaced=True
-                            yTmp=copy.deepcopy(y)
-                            yTmp['cluster']=clusterName
-                            if modeNoGap == False:
+                    if modeNoGap == False:
+                        replaced=False
+                        for y in listHypRefSegment:
+                            if y['cluster']!=clusterName:
+                                replaced=True
+                                yTmp=copy.deepcopy(y)
+                                yTmp['cluster']=clusterName
                                 actionsSegmentationSegmentDelete.append(copy.deepcopy(y)) 
                                 actionsIncrementalSegmentationSegmentDeleteTurn.append(copy.deepcopy(y))
-                            valueTmp=dropSegment(y,valueTmp)
-                            if modeNoGap == False:
+                                valueTmp=dropSegment(y,valueTmp)
                                 actionsSegmentationSegmentCreate.append(copy.deepcopy(Segment([valueRef['show'],yTmp['cluster'],yTmp['cluster_type'],yTmp['start'],yTmp['stop']],['show','cluster','cluster_type','start','stop']))) 
                                 actionsIncrementalSegmentationSegmentCreateTurn.append(copy.deepcopy(Segment([valueRef['show'],yTmp['cluster'],yTmp['cluster_type'],yTmp['start'],yTmp['stop']],['show','cluster','cluster_type','start','stop']))) 
-                            valueTmp.append_seg(yTmp)  
-                    if replaced:
-                        valueTmp.sort()
+                                valueTmp.append_seg(yTmp)  
+                        if replaced:
+                            valueTmp.sort()
                     # Merges among them if > 1
                     if len(listHypRefSegment)>1:
                         # Gets the new segments, modified by the previous steps
@@ -618,17 +621,27 @@ def automatonSegmentation(diarHyp,diarRef,diarUem=None,tolerance=0,modeNoGap=Fal
                                     listTmp.append(y)
                                 elif tolerance!=0 and y['start']>=(valueRef['start']-tolerance):
                                     listTmp.append(y)
-                        actionsSegmentationBoundaryMerge.append(copy.deepcopy([listTmp[0],listTmp[1]]))
-                        actionsIncrementalSegmentationBoundaryMergeTurn.append(copy.deepcopy([listTmp[0],listTmp[1]]))
-                        newSegment,valueTmp=mergeSegment(listTmp[0],listTmp[1],valueTmp)
+                        if not (not deleteBoundarySameConsecutiveSpk and listTmp[0]['cluster']==listTmp[1]['cluster']):
+                            actionsSegmentationBoundaryMerge.append(copy.deepcopy([listTmp[0],listTmp[1]]))
+                            actionsIncrementalSegmentationBoundaryMergeTurn.append(copy.deepcopy([listTmp[0],listTmp[1]]))
+                            if modeNoGap == True and listTmp[0]['cluster']!=listTmp[1]['cluster']:
+                                listTmp[1]['cluster']=listTmp[0]['cluster']
+                            newSegment,valueTmp=mergeSegment(listTmp[0],listTmp[1],valueTmp)
+                        else:
+                            newSegment=listTmp[1]
                         for y in range(2,len(listTmp)):
                             if modeNoGap == True:
                                 if not (Segment.intersection(newSegment,listTmp[y]) is not None or newSegment["stop"]==listTmp[y]["start"] or newSegment["start"]==listTmp[y]["stop"]):
                                     logging.error("Cannot have absence of a segment in Transcriber mode.")
                                     raise Exception("Absence of a segment.")
-                            actionsSegmentationBoundaryMerge.append(copy.deepcopy([newSegment,listTmp[y]]))
-                            actionsIncrementalSegmentationBoundaryMergeTurn.append(copy.deepcopy([newSegment,listTmp[y]]))
-                            newSegment,valueTmp=mergeSegment(newSegment,listTmp[y],valueTmp)
+                            if not (not deleteBoundarySameConsecutiveSpk and newSegment['cluster']==listTmp[y]['cluster']):
+                                actionsSegmentationBoundaryMerge.append(copy.deepcopy([newSegment,listTmp[y]]))
+                                actionsIncrementalSegmentationBoundaryMergeTurn.append(copy.deepcopy([newSegment,listTmp[y]]))
+                                if modeNoGap == True and newSegment['cluster']!=listTmp[y]['cluster']:
+                                    listTmp[y]['cluster']=newSegment['cluster']
+                                newSegment,valueTmp=mergeSegment(newSegment,listTmp[y],valueTmp)
+                            else:
+                                newSegment=listTmp[y]
         # Updates diarHyp
         diarHyp=valueTmp
 
@@ -709,8 +722,10 @@ def automatonSegmentation(diarHyp,diarRef,diarUem=None,tolerance=0,modeNoGap=Fal
 ## tolerance: In centiseconds
 ## diarFinal__clusterToDeleteAccordingToDiarRef: List of clusters to delete in the diarFinal only
 ## modeNoGap: Drops or not the segment actions (i.e. createSegment & deleteSegment)
-def automatonSegmentationAssignment(diarHyp,diarRef,diarUem=None,tolerance=0,modeNoGap=False,diarFinal__clusterToDeleteAccordingToDiarRef=list()):
-    assert isinstance(diarHyp,Diar) and isinstance(diarRef,Diar) and isinstance(modeNoGap,bool) and (diarUem is None or isinstance(diarUem,Diar)) and isinstance(tolerance,numbers.Number) and isinstance(diarFinal__clusterToDeleteAccordingToDiarRef,list)
+## deleteBoundarySameConsecutiveSpk: Whether we delete a boundary for two consecutive segments with the same speaker
+## deleteBoundaryMergeCluster: The action "delete a boundary" can merge two consecutive segments with different cluster names (it takes the name of the left/first segment)
+def automatonSegmentationAssignment(diarHyp,diarRef,diarUem=None,tolerance=0,modeNoGap=False,diarFinal__clusterToDeleteAccordingToDiarRef=list(),deleteBoundarySameConsecutiveSpk=False,deleteBoundaryMergeCluster=False):
+    assert isinstance(diarHyp,Diar) and isinstance(diarRef,Diar) and isinstance(modeNoGap,bool) and (diarUem is None or isinstance(diarUem,Diar)) and isinstance(tolerance,numbers.Number) and isinstance(diarFinal__clusterToDeleteAccordingToDiarRef,list) and isinstance(deleteBoundarySameConsecutiveSpk,bool) and isinstance(deleteBoundaryMergeCluster,bool)
     for u in diarFinal__clusterToDeleteAccordingToDiarRef:
         assert isinstance(u,str)
 
@@ -1056,13 +1071,11 @@ def automatonSegmentationAssignment(diarHyp,diarRef,diarUem=None,tolerance=0,mod
                             actionsIncrementalAssignmentCreateTurn.append(copy.deepcopy([valueRef['cluster'],z['cluster'],copy.deepcopy(z)]))
                     else:
                         if z['cluster'] == dictionary[valueRef['cluster']]:
-                            if (modeNoGap == True and idx==0) or (modeNoGap == False):
-                                actionsAssignmentNothing.append(copy.deepcopy(z))
-                                actionsIncrementalAssignmentNothingTurn.append(copy.deepcopy(z))
+                            actionsAssignmentNothing.append(copy.deepcopy(z))
+                            actionsIncrementalAssignmentNothingTurn.append(copy.deepcopy(z))
                         else:
-                            if (modeNoGap == True and idx==0) or (modeNoGap == False):
-                                actionsAssignmentChange.append(copy.deepcopy([dictionary[valueRef['cluster']],z]))
-                                actionsIncrementalAssignmentChangeTurn.append(copy.deepcopy([dictionary[valueRef['cluster']],z]))
+                            actionsAssignmentChange.append(copy.deepcopy([dictionary[valueRef['cluster']],z]))
+                            actionsIncrementalAssignmentChangeTurn.append(copy.deepcopy([dictionary[valueRef['cluster']],z]))
                             applyChange=True
                     if applyChange:
                         # Updates the diar for the merges afterward
@@ -1071,6 +1084,8 @@ def automatonSegmentationAssignment(diarHyp,diarRef,diarUem=None,tolerance=0,mod
                         valueTmp=dropSegment(z,valueTmp)
                         valueTmp.append_seg(segmentTmp)
                         valueTmp.sort()
+                    if deleteBoundaryMergeCluster:
+                        break
                 if not perfectBoundary:
                     # Gets the new segments, modified by the previous steps
                     listHypRefSegment=list()
@@ -1145,22 +1160,30 @@ def automatonSegmentationAssignment(diarHyp,diarRef,diarUem=None,tolerance=0,mod
                                     listTmp.append(y)
                                 elif tolerance!=0 and y['start']>=(valueRef['start']-tolerance):
                                     listTmp.append(y)
-                        if modeNoGap == True:
-                            clusterSelected=listTmp[0]['cluster']
-                        actionsSegmentationBoundaryMerge.append(copy.deepcopy([listTmp[0],listTmp[1]]))
-                        actionsIncrementalSegmentationBoundaryMergeTurn.append(copy.deepcopy([listTmp[0],listTmp[1]]))
-                        if modeNoGap == True:
-                            listTmp[1]['cluster']=clusterSelected
-                        newSegment,valueTmp=mergeSegment(listTmp[0],listTmp[1],valueTmp)
+                        if not (not deleteBoundarySameConsecutiveSpk and listTmp[0]['cluster']==listTmp[1]['cluster']):
+                            actionsSegmentationBoundaryMerge.append(copy.deepcopy([listTmp[0],listTmp[1]]))
+                            actionsIncrementalSegmentationBoundaryMergeTurn.append(copy.deepcopy([listTmp[0],listTmp[1]]))
+                            if modeNoGap == True and listTmp[0]['cluster']!=listTmp[1]['cluster']:
+                                listTmp[1]['cluster']=listTmp[0]['cluster']
+                            newSegment,valueTmp=mergeSegment(listTmp[0],listTmp[1],valueTmp)
+                        else:
+                            newSegment=listTmp[1]
                         for y in range(2,len(listTmp)):
                             if modeNoGap == True:
-                                listTmp[y]['cluster']=clusterSelected
                                 if not (Segment.intersection(newSegment,listTmp[y]) is not None or newSegment["stop"]==listTmp[y]["start"] or newSegment["start"]==listTmp[y]["stop"]):
                                     logging.error("Cannot have absence of a segment in Transcriber mode.")
                                     raise Exception("Absence of a segment.")
-                            actionsSegmentationBoundaryMerge.append(copy.deepcopy([newSegment,listTmp[y]]))
-                            actionsIncrementalSegmentationBoundaryMergeTurn.append(copy.deepcopy([newSegment,listTmp[y]]))
-                            newSegment,valueTmp=mergeSegment(newSegment,listTmp[y],valueTmp)                    
+                            if not (not deleteBoundarySameConsecutiveSpk and newSegment['cluster']==listTmp[y]['cluster']):
+                                actionsSegmentationBoundaryMerge.append(copy.deepcopy([newSegment,listTmp[y]]))
+                                actionsIncrementalSegmentationBoundaryMergeTurn.append(copy.deepcopy([newSegment,listTmp[y]]))
+                                if modeNoGap == True and newSegment['cluster']!=listTmp[y]['cluster']:
+                                    valueTmp=dropSegment(listTmp[y],valueTmp)
+                                    listTmp[y]['cluster']=newSegment['cluster']
+                                    valueTmp.append_seg(listTmp[y])
+                                    valueTmp.sort()
+                                newSegment,valueTmp=mergeSegment(newSegment,listTmp[y],valueTmp)
+                            else:
+                                newSegment=listTmp[y]                    
         # Updates diarHyp
         diarHyp=valueTmp
 

tutorials/README.md

+S4D tutorials
+===
+
+Here you will find short tutorials on how to use different components of S4D to train and run a complete speaker diarization system.
+
+1. [Train a PLDA model for i-vector clustering](tuto_1_iv_model.ipynb)
+2. [Perform a BIC diarization](tuto_2_diar_bic.ipynb)
+3. [Use i-vectors for speaker clustering](tuto_3_iv_plda_clustering.ipynb)
\ No newline at end of file

tutorials/data/seg/ubm_ester.seg

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