renamed csv2grid output with timestamps

code/csv2grid_bis.py

@@ -25,17 +25,14 @@ for a in range(0, len(df), slices_length):
     #finds the segment offset of the 100th transcription entry and stores it into var 
     #in milliseconds
     audio_offset = df_sliced['segment_offset'].max()
-
-    #finds the segment offset of the 100th transcription entry and stores it into var 
-    #in milliseconds
-    audio_offset = int(df_sliced.tail(1)['segment_offset'])
-
+    
     #extracts recording at desired length and exports it to new file
     recording_sliced = recording[audio_onset:audio_offset]
-    recording_sliced.export("outputs/csv2grid_output/BN{0}.wav".format(a), format='wav')
+    recording_sliced.export("outputs/csv2grid_output/BN-{0}-{1}.wav".format(audio_onset, audio_offset), format='wav')
     
     #create textgrid
     grid = pr.TextGrid(xmax = (audio_offset-audio_onset)/1000)
+
     #iterate through each row
     for speaker, segments in df_sliced.groupby('speaker_id'):
         aTier = grid.add_tier(speaker)
@@ -52,7 +49,7 @@ for a in range(0, len(df), slices_length):
                 False
               )
 
-        grid.to_file("outputs/csv2grid_output/BN{0}.TextGrid".format(a))
+        grid.to_file("outputs/csv2grid_output/BN-{0}-{1}.TextGrid".format(audio_onset, audio_offset))
     
     
     #the end cut for this iteration becomes the starting point for next iteration