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import nltk
from nltk.translate.meteor_score import meteor_score
from nltk.translate.bleu_score import corpus_bleu
from indicnlp.tokenize import indic_tokenize
import pandas as pd
import numpy as np
def configure_nltk():
nltk.download('punkt')
nltk.download('wordnet')
def tokenize_hindi(text):
return indic_tokenize.trivial_tokenize(text, lang='hi')
def calculate_meteor_score(ref, output):
ref_tokens = tokenize_hindi(ref)
output_tokens = tokenize_hindi(output)
return meteor_score([ref_tokens], output_tokens)
def calculate_bleu_score(ref, output):
ref_tokens = [tokenize_hindi(ref)]
output_tokens = tokenize_hindi(output)
return corpus_bleu(ref_tokens, [output_tokens])
def read_hindi_data(filepath):
hindi_df = pd.read_csv(filepath)
hindi_df = hindi_df.replace('नेन', np.nan)
hindi_df = hindi_df.dropna()
return hindi_df
def create_reference_df(hindi_df):
reference_df = pd.DataFrame()
for i in range(1, 3):
reference_df[f'Question{i}'] = hindi_df[f'Question{i}']
reference_df[f'Answer{i}'] = hindi_df[f'Answer{i}']
return reference_df
def select_first_n_rows(df, n=10):
return df.iloc[:n]
def calculate_scores(reference_df, n=10):
meteor_scores = []
bleu_scores = []
for i in range(1, 3):
ref_question_col = f'Question{i}'
ref_answer_col = f'Answer{i}'
output_question_col = f'Question{i}_hindi'
output_answer_col = f'Answer{i}_hindi'
for ref_question, output_question in zip(reference_df[ref_question_col], reference_df[output_question_col]):
meteor_scores.append(calculate_meteor_score(ref_question, output_question))
bleu_scores.append(calculate_bleu_score(ref_question, output_question))
for ref_answer, output_answer in zip(reference_df[ref_answer_col], reference_df[output_answer_col]):
meteor_scores.append(calculate_meteor_score(ref_answer, output_answer))
bleu_scores.append(calculate_bleu_score(ref_answer, output_answer))
average_meteor_score = sum(meteor_scores) / len(meteor_scores)
average_bleu_score = sum(bleu_scores) / len(bleu_scores)
return average_meteor_score, average_bleu_score
def main():
# Configure NLTK
configure_nltk()
# Read Hindi data
hindi_df = read_hindi_data('/content/Hindi_QnA.csv')
# Create reference dataframe
reference_df = create_reference_df(hindi_df)
# Select first 10 rows
reference_df_first10 = select_first_n_rows(reference_df)
# Calculate scores
average_meteor_score, average_bleu_score = calculate_scores(reference_df_first10)
print("Average METEOR Score:", average_meteor_score)
print("Average BLEU Score:", average_bleu_score)
if __name__ == "__main__":
main()
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