cer

funasr/metrics/wer.py

@@ -2,178 +2,189 @@ import os
 import numpy as np
 import sys
 import hydra
+from omegaconf import DictConfig, OmegaConf, ListConfig
+
 
 def compute_wer(ref_file,
                 hyp_file,
                 cer_file,
                 cn_postprocess=False,
                 ):
-    rst = {
-        'Wrd': 0,
-        'Corr': 0,
-        'Ins': 0,
-        'Del': 0,
-        'Sub': 0,
-        'Snt': 0,
-        'Err': 0.0,
-        'S.Err': 0.0,
-        'wrong_words': 0,
-        'wrong_sentences': 0
-    }
-
-    hyp_dict = {}
-    ref_dict = {}
-    with open(hyp_file, 'r') as hyp_reader:
-        for line in hyp_reader:
-            key = line.strip().split()[0]
-            value = line.strip().split()[1:]
-            if cn_postprocess:
-                value = value.replace(" ", "")
-                value = [x for x in value]
-                value = " ".join(value)
-            hyp_dict[key] = value
-    with open(ref_file, 'r') as ref_reader:
-        for line in ref_reader:
-            key = line.strip().split()[0]
-            value = line.strip().split()[1:]
-            if cn_postprocess:
-                value = value.replace(" ", "")
-                value = [x for x in value]
-                value = " ".join(value)
-            ref_dict[key] = value
-
-    cer_detail_writer = open(cer_file, 'w')
-    for hyp_key in hyp_dict:
-        if hyp_key in ref_dict:
-           out_item = compute_wer_by_line(hyp_dict[hyp_key], ref_dict[hyp_key])
-           rst['Wrd'] += out_item['nwords']
-           rst['Corr'] += out_item['cor']
-           rst['wrong_words'] += out_item['wrong']
-           rst['Ins'] += out_item['ins']
-           rst['Del'] += out_item['del']
-           rst['Sub'] += out_item['sub']
-           rst['Snt'] += 1
-           if out_item['wrong'] > 0:
-               rst['wrong_sentences'] += 1
-           cer_detail_writer.write(hyp_key + print_cer_detail(out_item) + '\n')
-           cer_detail_writer.write("ref:" + '\t' + " ".join(list(map(lambda x: x.lower(), ref_dict[hyp_key]))) + '\n')
-           cer_detail_writer.write("hyp:" + '\t' + " ".join(list(map(lambda x: x.lower(), hyp_dict[hyp_key]))) + '\n')
-           cer_detail_writer.flush()
+	rst = {
+		'Wrd': 0,
+		'Corr': 0,
+		'Ins': 0,
+		'Del': 0,
+		'Sub': 0,
+		'Snt': 0,
+		'Err': 0.0,
+		'S.Err': 0.0,
+		'wrong_words': 0,
+		'wrong_sentences': 0
+	}
+	
+	hyp_dict = {}
+	ref_dict = {}
+	with open(hyp_file, 'r') as hyp_reader:
+		for line in hyp_reader:
+			key = line.strip().split()[0]
+			value = line.strip().split()[1:]
+			if cn_postprocess:
+				value = " ".join(value)
+				value = value.replace(" ", "")
+				if value[0] == "请":
+					value = value[1:]
+				value = [x for x in value]
+			hyp_dict[key] = value
+	with open(ref_file, 'r') as ref_reader:
+		for line in ref_reader:
+			key = line.strip().split()[0]
+			value = line.strip().split()[1:]
+			if cn_postprocess:
+				value = " ".join(value)
+				value = value.replace(" ", "")
+				value = [x for x in value]
+			ref_dict[key] = value
+	
+	cer_detail_writer = open(cer_file, 'w')
+	for hyp_key in hyp_dict:
+		if hyp_key in ref_dict:
+			out_item = compute_wer_by_line(hyp_dict[hyp_key], ref_dict[hyp_key])
+			rst['Wrd'] += out_item['nwords']
+			rst['Corr'] += out_item['cor']
+			rst['wrong_words'] += out_item['wrong']
+			rst['Ins'] += out_item['ins']
+			rst['Del'] += out_item['del']
+			rst['Sub'] += out_item['sub']
+			rst['Snt'] += 1
+			if out_item['wrong'] > 0:
+				rst['wrong_sentences'] += 1
+			cer_detail_writer.write(hyp_key + print_cer_detail(out_item) + '\n')
+			cer_detail_writer.write("ref:" + '\t' + " ".join(list(map(lambda x: x.lower(), ref_dict[hyp_key]))) + '\n')
+			cer_detail_writer.write("hyp:" + '\t' + " ".join(list(map(lambda x: x.lower(), hyp_dict[hyp_key]))) + '\n')
+			cer_detail_writer.flush()
+	
+	if rst['Wrd'] > 0:
+		rst['Err'] = round(rst['wrong_words'] * 100 / rst['Wrd'], 2)
+	if rst['Snt'] > 0:
+		rst['S.Err'] = round(rst['wrong_sentences'] * 100 / rst['Snt'], 2)
+	
+	cer_detail_writer.write('\n')
+	cer_detail_writer.write("%WER " + str(rst['Err']) + " [ " + str(rst['wrong_words']) + " / " + str(rst['Wrd']) +
+	                        ", " + str(rst['Ins']) + " ins, " + str(rst['Del']) + " del, " + str(
+		rst['Sub']) + " sub ]" + '\n')
+	cer_detail_writer.write(
+		"%SER " + str(rst['S.Err']) + " [ " + str(rst['wrong_sentences']) + " / " + str(rst['Snt']) + " ]" + '\n')
+	cer_detail_writer.write("Scored " + str(len(hyp_dict)) + " sentences, " + str(
+		len(hyp_dict) - rst['Snt']) + " not present in hyp." + '\n')
+	
+	cer_detail_writer.close()
 
-    if rst['Wrd'] > 0:
-        rst['Err'] = round(rst['wrong_words'] * 100 / rst['Wrd'], 2)
-    if rst['Snt'] > 0:
-        rst['S.Err'] = round(rst['wrong_sentences'] * 100 / rst['Snt'], 2)
 
-    cer_detail_writer.write('\n')
-    cer_detail_writer.write("%WER " + str(rst['Err']) + " [ " + str(rst['wrong_words'])+ " / " + str(rst['Wrd']) +
-                            ", " + str(rst['Ins']) + " ins, " + str(rst['Del']) + " del, " + str(rst['Sub']) + " sub ]" + '\n')
-    cer_detail_writer.write("%SER " + str(rst['S.Err']) + " [ " + str(rst['wrong_sentences']) + " / " + str(rst['Snt']) + " ]" + '\n')
-    cer_detail_writer.write("Scored " + str(len(hyp_dict)) + " sentences, " + str(len(hyp_dict) - rst['Snt']) + " not present in hyp." + '\n')
-
-    cer_detail_writer.close()
-     
 def compute_wer_by_line(hyp,
                         ref):
-    hyp = list(map(lambda x: x.lower(), hyp))
-    ref = list(map(lambda x: x.lower(), ref))
-
-    len_hyp = len(hyp)
-    len_ref = len(ref)
-
-    cost_matrix = np.zeros((len_hyp + 1, len_ref + 1), dtype=np.int16)
-
-    ops_matrix = np.zeros((len_hyp + 1, len_ref + 1), dtype=np.int8)
-
-    for i in range(len_hyp + 1):
-        cost_matrix[i][0] = i
-    for j in range(len_ref + 1):
-        cost_matrix[0][j] = j
-
-    for i in range(1, len_hyp + 1):
-        for j in range(1, len_ref + 1):
-            if hyp[i - 1] == ref[j - 1]:
-                cost_matrix[i][j] = cost_matrix[i - 1][j - 1]
-            else:
-                substitution = cost_matrix[i - 1][j - 1] + 1
-                insertion = cost_matrix[i - 1][j] + 1
-                deletion = cost_matrix[i][j - 1] + 1
-
-                compare_val = [substitution, insertion, deletion]
+	hyp = list(map(lambda x: x.lower(), hyp))
+	ref = list(map(lambda x: x.lower(), ref))
+	
+	len_hyp = len(hyp)
+	len_ref = len(ref)
+	
+	cost_matrix = np.zeros((len_hyp + 1, len_ref + 1), dtype=np.int16)
+	
+	ops_matrix = np.zeros((len_hyp + 1, len_ref + 1), dtype=np.int8)
+	
+	for i in range(len_hyp + 1):
+		cost_matrix[i][0] = i
+	for j in range(len_ref + 1):
+		cost_matrix[0][j] = j
+	
+	for i in range(1, len_hyp + 1):
+		for j in range(1, len_ref + 1):
+			if hyp[i - 1] == ref[j - 1]:
+				cost_matrix[i][j] = cost_matrix[i - 1][j - 1]
+			else:
+				substitution = cost_matrix[i - 1][j - 1] + 1
+				insertion = cost_matrix[i - 1][j] + 1
+				deletion = cost_matrix[i][j - 1] + 1
+				
+				compare_val = [substitution, insertion, deletion]
+				
+				min_val = min(compare_val)
+				operation_idx = compare_val.index(min_val) + 1
+				cost_matrix[i][j] = min_val
+				ops_matrix[i][j] = operation_idx
+	
+	match_idx = []
+	i = len_hyp
+	j = len_ref
+	rst = {
+		'nwords': len_ref,
+		'cor': 0,
+		'wrong': 0,
+		'ins': 0,
+		'del': 0,
+		'sub': 0
+	}
+	while i >= 0 or j >= 0:
+		i_idx = max(0, i)
+		j_idx = max(0, j)
+		
+		if ops_matrix[i_idx][j_idx] == 0:  # correct
+			if i - 1 >= 0 and j - 1 >= 0:
+				match_idx.append((j - 1, i - 1))
+				rst['cor'] += 1
+			
+			i -= 1
+			j -= 1
+		
+		elif ops_matrix[i_idx][j_idx] == 2:  # insert
+			i -= 1
+			rst['ins'] += 1
+		
+		elif ops_matrix[i_idx][j_idx] == 3:  # delete
+			j -= 1
+			rst['del'] += 1
+		
+		elif ops_matrix[i_idx][j_idx] == 1:  # substitute
+			i -= 1
+			j -= 1
+			rst['sub'] += 1
+		
+		if i < 0 and j >= 0:
+			rst['del'] += 1
+		elif j < 0 and i >= 0:
+			rst['ins'] += 1
+	
+	match_idx.reverse()
+	wrong_cnt = cost_matrix[len_hyp][len_ref]
+	rst['wrong'] = wrong_cnt
+	
+	return rst
 
-                min_val = min(compare_val)
-                operation_idx = compare_val.index(min_val) + 1
-                cost_matrix[i][j] = min_val
-                ops_matrix[i][j] = operation_idx
-
-    match_idx = []
-    i = len_hyp
-    j = len_ref
-    rst = {
-        'nwords': len_ref,
-        'cor': 0,
-        'wrong': 0,
-        'ins': 0,
-        'del': 0,
-        'sub': 0
-    }
-    while i >= 0 or j >= 0:
-        i_idx = max(0, i)
-        j_idx = max(0, j)
-
-        if ops_matrix[i_idx][j_idx] == 0:  # correct
-            if i - 1 >= 0 and j - 1 >= 0:
-                match_idx.append((j - 1, i - 1))
-                rst['cor'] += 1
-
-            i -= 1
-            j -= 1
-
-        elif ops_matrix[i_idx][j_idx] == 2:  # insert
-            i -= 1
-            rst['ins'] += 1
-
-        elif ops_matrix[i_idx][j_idx] == 3:  # delete
-            j -= 1
-            rst['del'] += 1
-
-        elif ops_matrix[i_idx][j_idx] == 1:  # substitute
-            i -= 1
-            j -= 1
-            rst['sub'] += 1
-
-        if i < 0 and j >= 0:
-            rst['del'] += 1
-        elif j < 0 and i >= 0:
-            rst['ins'] += 1
-
-    match_idx.reverse()
-    wrong_cnt = cost_matrix[len_hyp][len_ref]
-    rst['wrong'] = wrong_cnt
-
-    return rst
 
 def print_cer_detail(rst):
-    return ("(" + "nwords=" + str(rst['nwords']) + ",cor=" + str(rst['cor'])
-            + ",ins=" + str(rst['ins']) + ",del=" + str(rst['del']) + ",sub="
-            + str(rst['sub']) + ") corr:" + '{:.2%}'.format(rst['cor']/rst['nwords'])
-            + ",cer:" + '{:.2%}'.format(rst['wrong']/rst['nwords']))
+	return ("(" + "nwords=" + str(rst['nwords']) + ",cor=" + str(rst['cor'])
+	        + ",ins=" + str(rst['ins']) + ",del=" + str(rst['del']) + ",sub="
+	        + str(rst['sub']) + ") corr:" + '{:.2%}'.format(rst['cor'] / rst['nwords'])
+	        + ",cer:" + '{:.2%}'.format(rst['wrong'] / rst['nwords']))
 
 
 @hydra.main(config_name=None, version_base=None)
 def main_hydra(cfg: DictConfig):
-    ref_file = cfg.get("ref_file", None)
-    hyp_file = cfg.get("hyp_file", None)
-    cer_file = cfg.get("cer_file", None)
-    cn_postprocess = cfg.get("cn_postprocess", False)
-    if ref_file is None or hyp_file is None or cer_file is None:
-        print("usage : python -m  funasr.metrics.wer ++ref_file=test.ref ++hyp_file=test.hyp ++cer_file=test.wer ++cn_postprocess=false")
-        sys.exit(0)
-        
-    compute_wer(ref_file, hyp_file, cer_file, cn_postprocess)
+	ref_file = cfg.get("ref_file", None)
+	hyp_file = cfg.get("hyp_file", None)
+	cer_file = cfg.get("cer_file", None)
+	cn_postprocess = cfg.get("cn_postprocess", False)
+	if ref_file is None or hyp_file is None or cer_file is None:
+		print(
+			"usage : python -m  funasr.metrics.wer ++ref_file=test.ref ++hyp_file=test.hyp ++cer_file=test.wer ++cn_postprocess=false")
+		sys.exit(0)
+	
+	compute_wer(ref_file, hyp_file, cer_file, cn_postprocess)
+
 
 if __name__ == '__main__':
-    main_hydra()
+	main_hydra()