Merge 0bf07d2214 into 013a21c70d

edit_utils.py

@@ -1,49 +1,120 @@
-def get_span(orig, new, editType):
-    orig_list = orig.split(" ")
-    new_list = new.split(" ")
-    
-    flag = False # this indicate whether the actual edit follow the specified editType
-    if editType == "deletion":
-        assert len(orig_list) > len(new_list), f"the edit type is deletion, but new is not shorter than original:\n new: {new}\n orig: {orig}"
-        diff = len(orig_list) - len(new_list)
-        for i, (o, n) in enumerate(zip(orig_list, new_list)):
-            if o != n: # assume the index of the first different word is the starting index of the orig_span
-            
-                orig_span = [i, i + diff - 1] # assume that the indices are starting and ending index of the deleted part
-                new_span = [i-1, i] # but for the new span, the starting and ending index is the two words that surround the deleted part
-                flag = True
-                break
+import re
 
 
-    elif editType == "insertion": 
-        assert len(orig_list) < len(new_list), f"the edit type is insertion, but the new is not longer than the original:\n new: {new}\n orig: {orig}"
-        diff = len(new_list) - len(orig_list)
-        for i, (o, n) in enumerate(zip(orig_list, new_list)):
-            if o != n: # insertion is just the opposite of deletion
-                new_span = [i, i + diff - 1] # NOTE if only inserted one word, s and e will be the same
-                orig_span = [i-1, i]
-                flag = True
-                break
+def levenshtein_distance(word1, word2):
+    len1, len2 = len(word1), len(word2)
+    # Initialize a matrix to store the edit distances, operations, and positions
+    dp = [[(0, "", []) for _ in range(len2 + 1)] for _ in range(len1 + 1)]
 
-    elif editType == "substitution":
-        new_span = []
-        orig_span = []
-        for i, (o, n) in enumerate(zip(orig_list, new_list)):
-            if o != n:
-                new_span = [i]
-                orig_span = [i]
-                break
-        assert len(new_span) == 1 and len(orig_span) == 1, f"new_span: {new_span}, orig_span: {orig_span}"
-        for j, (o, n) in enumerate(zip(orig_list[::-1], new_list[::-1])):
-            if o != n:
-                new_span.append(len(new_list) - j -1)
-                orig_span.append(len(orig_list) - j - 1)
-                flag = True
-                break
-    else:
-        raise RuntimeError(f"editType unknown: {editType}")
+    # Initialize the first row and column
+    for i in range(len1 + 1):
+        dp[i][0] = (i, "d" * i)
+    for j in range(len2 + 1):
+        dp[0][j] = (j, "i" * j)
 
-    if not flag:
-        raise RuntimeError(f"wrong editing with the specified edit type:\n original: {orig}\n new: {new}\n, editType: {editType}")
+    # Fill in the rest of the matrix
+    for i in range(1, len1 + 1):
+        for j in range(1, len2 + 1):
+            cost = 0 if word1[i - 1] == word2[j - 1] else 1
+            # Minimum of deletion, insertion, or substitution
+            deletion = dp[i - 1][j][0] + 1
+            insertion = dp[i][j - 1][0] + 1
+            substitution = dp[i - 1][j - 1][0] + cost
+            min_dist = min(deletion, insertion, substitution)
 
-    return orig_span, new_span    
+            # which operation led to the minimum distance
+            if min_dist == deletion:
+                operation = dp[i - 1][j][1] + "d"
+            elif min_dist == insertion:
+                operation = dp[i][j - 1][1] + "i"
+            else:
+                operation = dp[i - 1][j - 1][1] + ("s" if cost else "=")
+
+            dp[i][j] = (min_dist, operation)
+
+    # min edit distance, list of operations, positions of operations
+    return dp[len1][len2][0], dp[len1][len2][1]
+
+
+def extract_words(sentence):
+    words = re.findall(r"\b\w+\b", sentence)
+    return words
+
+# edge cases for spans of deletion, insertion, substitution
+def handle_delete(start, end, orig, new):
+    orig.append([start, end - 1])
+    new.append([start - 1, start])
+
+def handle_insert(start, end, orig, new):
+    temp_new = [start - 1, start]
+    orig.append(temp_new)
+    new.append(orig[-1])
+    orig[-1], new[-1] = new[-1], temp_new
+
+def handle_substitute(start, end, orig, new):
+    orig.append([start, end - 1])
+    new.append([start, end - 1])
+
+# editing the last index of the sentence is another edge case
+def handle_last_operation(prev_op, start, end, orig, new):
+    if prev_op == 'd':
+        handle_delete(start, end, orig, new)
+    elif prev_op == 'i':
+        handle_insert(start, end, orig, new)
+    elif prev_op == 's':
+        handle_substitute(start, end, orig, new)
+
+# adjust spans according to edge case expected output
+def adjust_last_span(operations, orig, new):
+    if operations[-1] == 'd':
+        new[-1] = [new[-1][0] - 1, new[-1][1] - 1]
+        orig[-1] = [orig[-1][0] - 1, orig[-1][0] - 1]
+    elif operations[-1] == 'i':
+        new[-1] = [new[-1][0] - 1, new[-1][1] - 1]
+        orig[-1] = [orig[-1][0] - 1, orig[-1][0]]
+
+def get_spans(operations):
+    orig = []
+    new = []
+    prev_op = None
+    start = 0
+    end = 0
+    for i, op in enumerate(operations):
+        # prevent span duplication of sequential edits of the same type
+        if op != '=':
+            if op != prev_op:
+                if prev_op:
+                    handle_last_operation(prev_op, start, end, orig, new)
+                prev_op = op
+                start = i
+            end = i + 1
+        else:
+            if prev_op:
+                handle_last_operation(prev_op, start, end, orig, new)
+                prev_op = None
+            start = end
+    # edge case of last operation
+    if prev_op:
+        handle_last_operation(prev_op, start, end, orig, new)
+    adjust_last_span(operations, orig, new)
+    return orig, new
+
+def get_edits(operations):
+    used_edits = []
+    prev_op = ''
+    for op in operations:
+        if op == 'i' and prev_op != 'i':
+            used_edits.append("insertion")
+        elif op == 'd' and prev_op != 'd':
+            used_edits.append("deletion")
+        elif op == 's' and prev_op != 's':
+            used_edits.append("substitution")
+        prev_op = op
+    return used_edits
+
+def parse_edit(orig_transcript, trgt_transcript):
+    word1 = extract_words(orig_transcript)
+    word2 = extract_words(trgt_transcript)
+    distance, operations = levenshtein_distance(word1, word2)
+    orig_span, new_span = get_spans(operations)
+    return operations, orig_span, new_span