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| # Import the required libraries | |
| import re | |
| from collections import Counter | |
| # The (mini)corpus for initial development originally comes from Wikipedia thanks to http://lukelindemann.com/wiki_corpus.html | |
| path_corpus = "Sundanese.txt" | |
| def words(text): return re.findall(r'\w+', text.lower()) | |
| WORDS = Counter(words(open(path_corpus, encoding='utf8').read())) | |
| def P(word, N=sum(WORDS.values())): | |
| "Probability of `word`." | |
| return WORDS[word] / N | |
| def correction(word): | |
| "Most probable spelling correction for word." | |
| return max(candidates(word), key=P) | |
| # Candidate model | |
| def candidates(word): | |
| "Generate possible spelling corrections for word." | |
| return (known([word]) or known(edits1(word)) or known(edits2(word)) or [word]) | |
| # Error model | |
| def known(words): | |
| "The subset of `words` that appear in the dictionary of WORDS." | |
| return set(w for w in words if w in WORDS) | |
| def edits1(word): | |
| "All edits that are one edit away from `word`." | |
| letters = 'abcdefghijklmnopqrstuvwxyz' | |
| splits = [(word[:i], word[i:]) for i in range(len(word) + 1)] | |
| deletes = [L + R[1:] for L, R in splits if R] | |
| transposes = [L + R[1] + R[0] + R[2:] for L, R in splits if len(R)>1] | |
| replaces = [L + c + R[1:] for L, R in splits if R for c in letters] | |
| inserts = [L + c + R for L, R in splits for c in letters] | |
| return set(deletes + transposes + replaces + inserts) | |
| def edits2(word): | |
| "All edits that are two edits away from `word`." | |
| return (e2 for e1 in edits1(word) for e2 in edits1(e1)) | |
| # Create a Gradio app | |
| import gradio as gr | |
| def correct_sentence(sentence): | |
| # Split the sentence into words | |
| words = re.findall(r'\b[\w\']+\b', sentence) | |
| # Correct the spelling of each word | |
| corrected_words = [] | |
| for word in words: | |
| corrected_word = correction(word) | |
| corrected_words.append(corrected_word) | |
| # Join the corrected words into a sentence | |
| corrected_sentence = ' '.join(corrected_words) | |
| return corrected_sentence | |
| app = gr.Interface(correct_sentence, [gr.inputs.Textbox()], gr.outputs.Textbox(), | |
| examples=["anying, kuer jangarr sirah sok hayanh dahar nu lada hasuem."], | |
| title="Sundanese spell-checker app", | |
| description="This app check the Sundanese spell based on the probabilty theory.") | |
| app.launch() |