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| """
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| Shared utilities for WER evaluation scripts.
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| """
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| import logging
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|
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| import numpy as np
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| from jiwer import compute_measures
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| def process_one(hypothesis: str, truth: str, post_process, lang: str = None) -> dict:
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| """
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| Computes WER and related metrics for a single hypothesis-truth pair.
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| Args:
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| hypothesis (str): The transcribed text from the ASR model.
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| truth (str): The ground truth transcript.
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| post_process (callable): Text normalization function defined by each script.
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| Signature: post_process(text, lang) or post_process(text).
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| lang (str): The language code for post_process. Pass None if post_process
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| does not accept a lang argument.
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| Returns:
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| dict: A dict containing:
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| - truth (str): Post-processed ground truth text.
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| - hypothesis (str): Post-processed hypothesis text.
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| - wer (float): Word Error Rate.
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| - substitutions (int): Number of substitutions.
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| - deletions (int): Number of deletions.
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| - insertions (int): Number of insertions.
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| - word_num (int): Number of words in the post-processed ground truth.
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| """
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| if lang is not None:
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| truth_processed = post_process(truth, lang)
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| hypothesis_processed = post_process(hypothesis, lang)
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| else:
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| truth_processed = post_process(truth)
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| hypothesis_processed = post_process(hypothesis)
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| measures = compute_measures(truth_processed, hypothesis_processed)
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| word_num = len(truth_processed.split(" "))
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| return {
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| "truth": truth_processed,
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| "hypo": hypothesis_processed,
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| "wer": measures["wer"],
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| "substitutions": measures["substitutions"],
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| "deletions": measures["deletions"],
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| "insertions": measures["insertions"],
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| "word_num": word_num,
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| }
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| def log_metrics(fout, prefix, i_list, d_list, s_list, w_total, ndigits=2):
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| """Log weighted WER metrics for a subset of results."""
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| metrics_wer = round(
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| (np.sum(s_list) + np.sum(d_list) + np.sum(i_list)) / w_total * 100, ndigits
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| )
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| metrics_inse = np.sum(i_list)
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| metrics_dele = np.sum(d_list)
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| metrics_subs = np.sum(s_list)
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| logging.info(f"{prefix} WER: {metrics_wer}%")
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| logging.info(
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| f"{prefix} Errors: {metrics_inse} ins, {metrics_dele} del, "
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| f"{metrics_subs} sub / {w_total} words"
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| )
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| if fout:
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| fout.write(f"{prefix} WER: {metrics_wer}%\n")
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| fout.write(
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| f"{prefix} Errors: {metrics_inse} ins, {metrics_dele} del, "
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| f"{metrics_subs} sub / {w_total} words\n"
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| )
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| return metrics_wer
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|
|
