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tool.py
CHANGED
@@ -1,7 +1,7 @@
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from smolagents.tools import Tool
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import string
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import json
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import pronouncing
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class WordPhoneTool(Tool):
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name = "word_phonetic_analyzer"
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Can also compare two words for phonetic similarity and rhyming."""
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inputs = {'word': {'type': 'string', 'description': 'Primary word to analyze for pronunciation patterns'}, 'compare_to': {'type': 'string', 'description': 'Optional word to compare against for similarity scoring', 'nullable': True}, 'custom_phones': {'type': 'object', 'description': 'Optional dictionary of custom word pronunciations', 'nullable': True}}
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output_type = "string"
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def _get_vowel_groups(self):
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groups = []
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for
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return groups
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@@ -29,24 +39,112 @@ class WordPhoneTool(Tool):
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return phones[0] if phones else None
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def _get_last_syllable(self, phones):
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last_vowel_idx = -1
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last_vowel = None
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vowel_groups = self._get_vowel_groups()
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for i in
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for
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base_phone += char
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for group in vowel_groups:
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if base_phone in group:
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last_vowel_idx = i
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last_vowel = base_phone
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break
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if last_vowel_idx == -1:
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return None, []
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def _strip_stress(self, phones):
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result = []
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for phone in phones:
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stripped =
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for char in phone:
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if char not in "012":
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stripped += char
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result.append(stripped)
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return result
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def _vowels_match(self, v1, v2):
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for char in v1:
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if char not in "012":
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v1_stripped += char
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for char in v2:
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if char not in "012":
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v2_stripped += char
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if v1_stripped == v2_stripped:
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return True
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if v1_stripped in group and v2_stripped in group:
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return True
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return False
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def
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#
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word1_end = []
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word2_end = []
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matched = 0
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common_length = 0
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end1_clean = []
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end2_clean = []
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i = 0 # Initialize i for loop variable
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phone_list1 = phones1.split()
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phone_list2 = phones2.split()
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# Get
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result2 = self._get_last_syllable(phone_list2)
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last_vowel1, word1_end = result1
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last_vowel2, word2_end = result2
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# Calculate
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max_phones = max(len(phone_list1), len(phone_list2))
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length_score = 1.0 if phone_diff == 0 else 1.0 - (phone_diff / max_phones)
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# Calculate
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if last_vowel1 and last_vowel2:
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if self._vowels_match(last_vowel1, last_vowel2):
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end1_clean = self._strip_stress(word1_end)
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end2_clean = self._strip_stress(word2_end)
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if end1_clean == end2_clean:
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rhyme_score = 1.0 # Perfect rhyme, capped at 1.0
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else:
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# Partial rhyme based on ending similarity
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common_length = min(len(end1_clean), len(end2_clean))
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matched = 0
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for i in range(common_length):
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if end1_clean[i] == end2_clean[i]:
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matched += 1
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rhyme_score = 0.6 * (matched / max(len(end1_clean), len(end2_clean)))
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# Calculate stress pattern similarity
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stress1 = pronouncing.stresses(phones1)
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stress2 = pronouncing.stresses(phones2)
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stress_score = 1.0 if stress1 == stress2 else 0.5
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#
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(rhyme_score *
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(
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(
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)
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# Ensure total similarity is capped at 1.0
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total_similarity = min(1.0, total_similarity)
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return {
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"similarity": round(
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"rhyme_score": round(rhyme_score, 3),
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"length_score": round(length_score, 3),
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"
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}
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def forward(self, word, compare_to=None, custom_phones=None):
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import json
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import string
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import pronouncing
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word_last_vowel = None
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compare_last_vowel = None
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word_end = []
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compare_end = []
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is_rhyme = False
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word_clean = word.lower()
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word_clean = word_clean.strip(string.punctuation)
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primary_phones = self._get_word_phones(word_clean, custom_phones)
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if not primary_phones:
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'syllable_count': pronouncing.syllable_count(primary_phones),
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'phones': primary_phones.split(),
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'stresses': pronouncing.stresses(primary_phones),
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'phone_count': len(primary_phones.split())
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}
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}
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if compare_to:
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compare_clean = compare_to.lower()
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compare_clean = compare_clean.strip(string.punctuation)
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compare_phones = self._get_word_phones(compare_clean, custom_phones)
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if not compare_phones:
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'error': f'Comparison word "{compare_clean}" not found in dictionary or custom phones'
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}
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else:
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#
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word_result = self._get_last_syllable(primary_phones.split())
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compare_result = self._get_last_syllable(compare_phones.split())
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word_last_vowel, word_end = word_result
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compare_last_vowel, compare_end = compare_result
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#
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if word_last_vowel and compare_last_vowel:
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if self._vowels_match(word_last_vowel, compare_last_vowel):
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word_end_clean = self._strip_stress(word_end)
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if word_end_clean == compare_end_clean:
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is_rhyme = True
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#
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word_syl_count = pronouncing.syllable_count(primary_phones)
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compare_syl_count = pronouncing.syllable_count(compare_phones)
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'syllable_count': compare_syl_count,
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'phones': compare_phones.split(),
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'stresses': pronouncing.stresses(compare_phones),
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'phone_count': len(compare_phones.split())
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},
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'comparison_stats': {
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'
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'same_syllable_count': word_syl_count == compare_syl_count,
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'same_stress_pattern': pronouncing.stresses(primary_phones) == pronouncing.stresses(compare_phones),
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'syllable_difference': abs(word_syl_count - compare_syl_count),
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}
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}
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# Calculate detailed similarity scores
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similarity_result = self._calculate_similarity(
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word_clean, primary_phones,
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compare_clean, compare_phones
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from smolagents.tools import Tool
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import pronouncing
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import json
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import string
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class WordPhoneTool(Tool):
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name = "word_phonetic_analyzer"
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Can also compare two words for phonetic similarity and rhyming."""
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inputs = {'word': {'type': 'string', 'description': 'Primary word to analyze for pronunciation patterns'}, 'compare_to': {'type': 'string', 'description': 'Optional word to compare against for similarity scoring', 'nullable': True}, 'custom_phones': {'type': 'object', 'description': 'Optional dictionary of custom word pronunciations', 'nullable': True}}
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output_type = "string"
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RHYME_WEIGHT = 0.6
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PHONE_SEQUENCE_WEIGHT = 0.3
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LENGTH_WEIGHT = 0.1
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PHONE_GROUPS = "M,N,NG|P,B|T,D|K,G|F,V|TH,DH|S,Z|SH,ZH|L,R|W,Y|IY,IH|UW,UH|EH,AH|AO,AA|AE,AH|AY,EY|OW,UW"
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def _get_vowel_groups(self):
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"""Get vowel groups for comparison."""
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groups = []
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vowel_parts = self.PHONE_GROUPS.split('|')
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for part in vowel_parts:
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is_vowel = False
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for vowel in 'AEIOU':
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if vowel in part:
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is_vowel = True
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break
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if is_vowel:
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groups.append(part.split(','))
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return groups
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return phones[0] if phones else None
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def _get_primary_vowel(self, phones):
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"""Get the primary stressed vowel from phone list."""
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for phone_str in phones:
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is_vowel_with_stress = False
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if '1' in phone_str:
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for vowel in 'AEIOU':
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if vowel in phone_str:
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is_vowel_with_stress = True
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break
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if is_vowel_with_stress:
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return phone_str.rstrip('012')
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return None
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def _get_phone_type(self, phone):
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"""Get the broad category of a phone."""
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# Strip stress markers
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phone = phone.rstrip('012')
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# Vowels
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is_vowel = False
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for vowel in 'AEIOU':
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if vowel in phone:
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is_vowel = True
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break
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if is_vowel:
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return 'vowel'
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# Initialize fixed sets for categories
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nasals = {'M', 'N', 'NG'}
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stops = {'P', 'B', 'T', 'D', 'K', 'G'}
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fricatives = {'F', 'V', 'TH', 'DH', 'S', 'Z', 'SH', 'ZH'}
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liquids = {'L', 'R'}
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glides = {'W', 'Y'}
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if phone in nasals:
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return 'nasal'
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if phone in stops:
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return 'stop'
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if phone in fricatives:
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return 'fricative'
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if phone in liquids:
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return 'liquid'
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if phone in glides:
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return 'glide'
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return 'other'
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def _phones_are_similar(self, phone1, phone2):
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"""Check if two phones are similar enough to be considered rhyming."""
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# Strip stress markers
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p1 = phone1.rstrip('012')
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p2 = phone2.rstrip('012')
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# Exact match
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if p1 == p2:
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return True
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# Check similarity groups
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for group_str in self.PHONE_GROUPS.split('|'):
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group = group_str.split(',')
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if p1 in group and p2 in group:
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return True
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return False
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def _get_phone_similarity(self, phone1, phone2):
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"""Calculate similarity between two phones."""
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# Initialize variables
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p1 = phone1.rstrip('012')
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p2 = phone2.rstrip('012')
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# Exact match
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if p1 == p2:
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return 1.0
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# Check similarity groups
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for group_str in self.PHONE_GROUPS.split('|'):
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group = group_str.split(',')
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if p1 in group and p2 in group:
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return 0.7
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# Check broader categories
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if self._get_phone_type(p1) == self._get_phone_type(p2):
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return 0.3
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return 0.0
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def _get_last_syllable(self, phones):
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"""Get the last vowel and remaining consonants (for rhyming analysis)."""
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last_vowel_idx = -1
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last_vowel = None
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for i, phone in enumerate(phones):
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base_phone = phone.rstrip('012')
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is_vowel = False
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for vowel in 'AEIOU':
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if vowel in base_phone:
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is_vowel = True
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break
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if is_vowel:
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last_vowel_idx = i
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last_vowel = base_phone
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if last_vowel_idx == -1:
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return None, []
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def _strip_stress(self, phones):
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"""Remove stress markers from phones."""
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result = []
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for phone in phones:
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stripped = phone.rstrip('012')
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result.append(stripped)
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return result
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def _vowels_match(self, v1, v2):
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"""Check if vowels are similar enough to rhyme."""
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v1_stripped = v1.rstrip('012')
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v2_stripped = v2.rstrip('012')
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173 |
if v1_stripped == v2_stripped:
|
174 |
return True
|
175 |
|
176 |
+
for group_str in self.PHONE_GROUPS.split('|'):
|
177 |
+
group = group_str.split(',')
|
178 |
if v1_stripped in group and v2_stripped in group:
|
179 |
return True
|
180 |
return False
|
181 |
|
182 |
|
183 |
+
def _get_rhyme_score(self, phones1, phones2):
|
184 |
+
"""Calculate rhyme score based on matching phones after primary stressed vowel."""
|
185 |
+
# Find primary stressed vowel position in both words
|
186 |
+
pos1 = -1
|
187 |
+
pos2 = -1
|
188 |
+
|
189 |
+
for i, phone in enumerate(phones1):
|
190 |
+
is_stressed_vowel = False
|
191 |
+
if '1' in phone:
|
192 |
+
for vowel in 'AEIOU':
|
193 |
+
if vowel in phone:
|
194 |
+
is_stressed_vowel = True
|
195 |
+
break
|
196 |
+
if is_stressed_vowel:
|
197 |
+
pos1 = i
|
198 |
+
break
|
199 |
+
|
200 |
+
for i, phone in enumerate(phones2):
|
201 |
+
is_stressed_vowel = False
|
202 |
+
if '1' in phone:
|
203 |
+
for vowel in 'AEIOU':
|
204 |
+
if vowel in phone:
|
205 |
+
is_stressed_vowel = True
|
206 |
+
break
|
207 |
+
if is_stressed_vowel:
|
208 |
+
pos2 = i
|
209 |
+
break
|
210 |
+
|
211 |
+
if pos1 == -1 or pos2 == -1:
|
212 |
+
return 0.0
|
213 |
+
|
214 |
+
# Get all phones after and including the stressed vowel
|
215 |
+
rhyme_part1 = phones1[pos1:]
|
216 |
+
rhyme_part2 = phones2[pos2:]
|
217 |
|
218 |
+
# If lengths are too different, not a good rhyme
|
219 |
+
if abs(len(rhyme_part1) - len(rhyme_part2)) > 1:
|
220 |
+
return 0.0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
221 |
|
222 |
+
# Calculate similarity score for rhyming part
|
223 |
+
similarity_count = 0
|
224 |
+
max_compare = min(len(rhyme_part1), len(rhyme_part2))
|
225 |
+
|
226 |
+
for i in range(max_compare):
|
227 |
+
if self._phones_are_similar(rhyme_part1[i], rhyme_part2[i]):
|
228 |
+
similarity_count += 1
|
229 |
+
|
230 |
+
# Return score based on how many phones were similar
|
231 |
+
return similarity_count / max(len(rhyme_part1), len(rhyme_part2)) if max(len(rhyme_part1), len(rhyme_part2)) > 0 else 0.0
|
232 |
+
|
233 |
+
|
234 |
+
def _calculate_phone_sequence_similarity(self, phones1, phones2):
|
235 |
+
"""Calculate similarity based on matching phones in sequence."""
|
236 |
+
if not phones1 or not phones2:
|
237 |
+
return 0.0
|
238 |
+
|
239 |
+
total_similarity = 0.0
|
240 |
+
comparisons = max(len(phones1), len(phones2))
|
241 |
+
|
242 |
+
# Compare each position
|
243 |
+
for i in range(min(len(phones1), len(phones2))):
|
244 |
+
similarity = self._get_phone_similarity(phones1[i], phones2[i])
|
245 |
+
total_similarity += similarity
|
246 |
+
|
247 |
+
return total_similarity / comparisons if comparisons > 0 else 0.0
|
248 |
+
|
249 |
+
|
250 |
+
def _calculate_length_similarity(self, phones1, phones2):
|
251 |
+
"""Calculate similarity based on phone length."""
|
252 |
+
max_length = max(len(phones1), len(phones2))
|
253 |
+
length_diff = abs(len(phones1) - len(phones2))
|
254 |
+
return 1.0 - (length_diff / max_length) if max_length > 0 else 0.0
|
255 |
+
|
256 |
+
|
257 |
+
def _calculate_similarity(self, word1, phones1, word2, phones2):
|
258 |
+
"""Calculate similarity based on multiple factors."""
|
259 |
phone_list1 = phones1.split()
|
260 |
phone_list2 = phones2.split()
|
261 |
|
262 |
+
# Get rhyme score (most important)
|
263 |
+
rhyme_score = self._get_rhyme_score(phone_list1, phone_list2)
|
|
|
|
|
|
|
264 |
|
265 |
+
# Calculate phone sequence similarity
|
266 |
+
phone_sequence_score = self._calculate_phone_sequence_similarity(phone_list1, phone_list2)
|
|
|
|
|
267 |
|
268 |
+
# Calculate length similarity score
|
269 |
+
length_score = self._calculate_length_similarity(phone_list1, phone_list2)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
270 |
|
271 |
+
# Combined weighted score
|
272 |
+
similarity = (
|
273 |
+
(rhyme_score * self.RHYME_WEIGHT) +
|
274 |
+
(phone_sequence_score * self.PHONE_SEQUENCE_WEIGHT) +
|
275 |
+
(length_score * self.LENGTH_WEIGHT)
|
276 |
)
|
277 |
|
|
|
|
|
|
|
278 |
return {
|
279 |
+
"similarity": round(similarity, 3),
|
280 |
"rhyme_score": round(rhyme_score, 3),
|
281 |
+
"phone_sequence_score": round(phone_sequence_score, 3),
|
282 |
"length_score": round(length_score, 3),
|
283 |
+
"details": {
|
284 |
+
"primary_vowel1": self._get_primary_vowel(phone_list1),
|
285 |
+
"primary_vowel2": self._get_primary_vowel(phone_list2),
|
286 |
+
"phone_count1": len(phone_list1),
|
287 |
+
"phone_count2": len(phone_list2),
|
288 |
+
"is_rhyme": rhyme_score > 0.8,
|
289 |
+
"stress_pattern1": self._get_stress_pattern(phones1),
|
290 |
+
"stress_pattern2": self._get_stress_pattern(phones2)
|
291 |
+
}
|
292 |
}
|
293 |
|
294 |
|
295 |
+
def _get_stress_pattern(self, phones):
|
296 |
+
"""Extract stress pattern from phones."""
|
297 |
+
import pronouncing
|
298 |
+
return pronouncing.stresses(phones)
|
299 |
+
|
300 |
+
|
301 |
def forward(self, word, compare_to=None, custom_phones=None):
|
302 |
import json
|
303 |
import string
|
304 |
import pronouncing
|
305 |
|
306 |
+
word_clean = word.lower().strip(string.punctuation)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
307 |
primary_phones = self._get_word_phones(word_clean, custom_phones)
|
308 |
|
309 |
if not primary_phones:
|
|
|
321 |
'syllable_count': pronouncing.syllable_count(primary_phones),
|
322 |
'phones': primary_phones.split(),
|
323 |
'stresses': pronouncing.stresses(primary_phones),
|
324 |
+
'phone_count': len(primary_phones.split()),
|
325 |
+
'primary_vowel': self._get_primary_vowel(primary_phones.split())
|
326 |
}
|
327 |
}
|
328 |
|
329 |
if compare_to:
|
330 |
+
compare_clean = compare_to.lower().strip(string.punctuation)
|
|
|
331 |
compare_phones = self._get_word_phones(compare_clean, custom_phones)
|
332 |
|
333 |
if not compare_phones:
|
|
|
335 |
'error': f'Comparison word "{compare_clean}" not found in dictionary or custom phones'
|
336 |
}
|
337 |
else:
|
338 |
+
# Initialize variables for traditional rhyme analysis
|
339 |
+
word_last_vowel = None
|
340 |
+
compare_last_vowel = None
|
341 |
+
word_end = []
|
342 |
+
compare_end = []
|
343 |
+
|
344 |
+
# Get rhyme components for traditional rhyme analysis
|
345 |
word_result = self._get_last_syllable(primary_phones.split())
|
346 |
compare_result = self._get_last_syllable(compare_phones.split())
|
|
|
|
|
347 |
|
348 |
+
# Unpack results with explicit assignment
|
349 |
+
if word_result and len(word_result) == 2:
|
350 |
+
word_last_vowel = word_result[0]
|
351 |
+
word_end = word_result[1]
|
352 |
+
|
353 |
+
if compare_result and len(compare_result) == 2:
|
354 |
+
compare_last_vowel = compare_result[0]
|
355 |
+
compare_end = compare_result[1]
|
356 |
+
|
357 |
+
# Calculate if words rhyme using traditional method
|
358 |
+
is_rhyme = False
|
359 |
if word_last_vowel and compare_last_vowel:
|
360 |
if self._vowels_match(word_last_vowel, compare_last_vowel):
|
361 |
word_end_clean = self._strip_stress(word_end)
|
|
|
363 |
if word_end_clean == compare_end_clean:
|
364 |
is_rhyme = True
|
365 |
|
366 |
+
# Basic analysis
|
367 |
word_syl_count = pronouncing.syllable_count(primary_phones)
|
368 |
compare_syl_count = pronouncing.syllable_count(compare_phones)
|
369 |
|
|
|
373 |
'syllable_count': compare_syl_count,
|
374 |
'phones': compare_phones.split(),
|
375 |
'stresses': pronouncing.stresses(compare_phones),
|
376 |
+
'phone_count': len(compare_phones.split()),
|
377 |
+
'primary_vowel': self._get_primary_vowel(compare_phones.split())
|
378 |
},
|
379 |
'comparison_stats': {
|
380 |
+
'traditional_rhyme': is_rhyme,
|
381 |
'same_syllable_count': word_syl_count == compare_syl_count,
|
382 |
'same_stress_pattern': pronouncing.stresses(primary_phones) == pronouncing.stresses(compare_phones),
|
383 |
'syllable_difference': abs(word_syl_count - compare_syl_count),
|
|
|
385 |
}
|
386 |
}
|
387 |
|
388 |
+
# Calculate detailed similarity scores with new algorithm
|
389 |
similarity_result = self._calculate_similarity(
|
390 |
word_clean, primary_phones,
|
391 |
compare_clean, compare_phones
|