Updated example docstrings

phone_distance.py

@@ -73,12 +73,12 @@ Returns:
 Examples:
     Compare articulatory differences in voicing in "bob" vs. "pop" and different pronunciations of "the":
 >>> phone_distance = evaluate.load("ginic/phone_distance")
->>> phone_distance.compute(predictions=["bob", "θə"], references=["pop", "θi"])
+>>> phone_distance.compute(predictions=["bob", "ði"], references=["pop", "ðə"])
 {'phone_error_rates': [0.6666666666666666, 0.5], 'mean_phone_error_rate': 0.5833333333333333, 'phone_feature_error_rates': [0.08333333333333333, 0.125], 'mean_phone_feature_error_rates': 0.10416666666666666, 'feature_error_rates': [0.027777777777777776, 0.0625], 'mean_feature_error_rates': 0.04513888888888889}
 
     Normalize PFER by the length of string with largest number of phones: 
 >>> phone_distance = evaluate.load("ginic/phone_distance")
->>> phone_distance.compute(predictions=["bob", "θə"], references=["pop", "θi"], is_normalize_pfer=True)
+>>> phone_distance.compute(predictions=["bob", "ði"], references=["pop", "ðə"], is_normalize_pfer=True)
 
 """
 
@@ -91,6 +91,11 @@ def phone_error_rate(prediction:str, reference: str, distance_computer:panphon.d
 
     Returns:
         float:  the phone error rate
+
+    >>> phone_error_rate("bob", "po", panphon.distance.Distance())
+    1.0
+    >>> phone_error_rate("ði", "ðə", panphon.distance.Distance())
+    0.5
     """
     if reference: # Can only be computed when the length of the reference greater than 0 
         pred_phones = distance_computer.fm.ipa_segs(prediction)