好きな歌の歌詞を解析して近い曲を探す

import nltk
from nltk.sentiment import SentimentIntensityAnalyzer
from gensim import corpora, models
from fugashi import Tagger
from lyricsgenius import Genius

# 初期化
genius = Genius("あなたの-genius-アクセストークン")
sia = SentimentIntensityAnalyzer()
tagger = Tagger()

# 曲のタイトルを入力
song_title = input("好きな曲のタイトルを入力してください: ")

# 歌詞を取得
song = genius.search_song(song_title)
lyrics = song.lyrics

# 感情分析
sentiment = sia.polarity_scores(lyrics)

# 主題分析とキーワード抽出
words = [word.surface for word in tagger.parse(lyrics)]
dictionary = corpora.Dictionary([words])
corpus = [dictionary.doc2bow(words)]
lda_model = models.LdaModel(corpus, num_topics=1, id2word=dictionary)
keywords = [dictionary[id] for id, _ in lda_model.get_topic_terms(0)]

# 類似曲を検索
similar_songs = genius.search_songs(" ".join(keywords))[:10]

# 類似曲を分析
similarities = []
for similar_song in similar_songs["hits"]:
    similar_lyrics = genius.search_song(similar_song["result"]["title"]).lyrics
    similar_sentiment = sia.polarity_scores(similar_lyrics)
    similar_words = [word.surface for word in tagger.parse(similar_lyrics)]
    similar_corpus = [dictionary.doc2bow(similar_words)]
    similar_lda_model = models.LdaModel(similar_corpus, num_topics=1, id2word=dictionary)
    similar_keywords = [dictionary[id] for id, _ in similar_lda_model.get_topic_terms(0)]
    similarities.append((similar_song["result"]["title"], similar_sentiment, similar_keywords))

# 最も類似した曲を見つける
most_similar_song = max(similarities, key=lambda x: (x[1]["compound"], len(set(keywords) & set(x[2]))))

# 最も類似した曲を提案する
print("最も類似した曲は:", most_similar_song[0])