mirror of
https://github.com/modelscope/FunASR
synced 2025-09-15 14:48:36 +08:00
360 lines
12 KiB
Python
360 lines
12 KiB
Python
# Copyright (c) Alibaba, Inc. and its affiliates.
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import os
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import struct
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from typing import Any, Dict, List, Union
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import torchaudio
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import librosa
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import numpy as np
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import pkg_resources
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from modelscope.utils.logger import get_logger
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logger = get_logger()
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green_color = '\033[1;32m'
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red_color = '\033[0;31;40m'
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yellow_color = '\033[0;33;40m'
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end_color = '\033[0m'
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global_asr_language = 'zh-cn'
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SUPPORT_AUDIO_TYPE_SETS = ['flac', 'mp3', 'ogg', 'opus', 'wav', 'pcm']
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def get_version():
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return float(pkg_resources.get_distribution('easyasr').version)
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def sample_rate_checking(audio_in: Union[str, bytes], audio_format: str):
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r_audio_fs = None
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if audio_format == 'wav' or audio_format == 'scp':
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r_audio_fs = get_sr_from_wav(audio_in)
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elif audio_format == 'pcm' and isinstance(audio_in, bytes):
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r_audio_fs = get_sr_from_bytes(audio_in)
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return r_audio_fs
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def type_checking(audio_in: Union[str, bytes],
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audio_fs: int = None,
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recog_type: str = None,
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audio_format: str = None):
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r_recog_type = recog_type
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r_audio_format = audio_format
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r_wav_path = audio_in
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if isinstance(audio_in, str):
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assert os.path.exists(audio_in), f'wav_path:{audio_in} does not exist'
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elif isinstance(audio_in, bytes):
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assert len(audio_in) > 0, 'audio in is empty'
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r_audio_format = 'pcm'
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r_recog_type = 'wav'
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if audio_in is None:
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# for raw_inputs
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r_recog_type = 'wav'
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r_audio_format = 'pcm'
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if r_recog_type is None and audio_in is not None:
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# audio_in is wav, recog_type is wav_file
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if os.path.isfile(audio_in):
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audio_type = os.path.basename(audio_in).lower()
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for support_audio_type in SUPPORT_AUDIO_TYPE_SETS:
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if audio_type.rfind(".{}".format(support_audio_type)) >= 0:
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r_recog_type = 'wav'
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r_audio_format = 'wav'
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if audio_type.rfind(".scp") >= 0:
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r_recog_type = 'wav'
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r_audio_format = 'scp'
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if r_recog_type is None:
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raise NotImplementedError(
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f'Not supported audio type: {audio_type}')
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# recog_type is datasets_file
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elif os.path.isdir(audio_in):
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dir_name = os.path.basename(audio_in)
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if 'test' in dir_name:
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r_recog_type = 'test'
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elif 'dev' in dir_name:
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r_recog_type = 'dev'
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elif 'train' in dir_name:
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r_recog_type = 'train'
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if r_audio_format is None:
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if find_file_by_ends(audio_in, '.ark'):
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r_audio_format = 'kaldi_ark'
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elif find_file_by_ends(audio_in, '.wav') or find_file_by_ends(
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audio_in, '.WAV'):
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r_audio_format = 'wav'
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elif find_file_by_ends(audio_in, '.records'):
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r_audio_format = 'tfrecord'
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if r_audio_format == 'kaldi_ark' and r_recog_type != 'wav':
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# datasets with kaldi_ark file
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r_wav_path = os.path.abspath(os.path.join(r_wav_path, '../'))
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elif r_audio_format == 'tfrecord' and r_recog_type != 'wav':
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# datasets with tensorflow records file
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r_wav_path = os.path.abspath(os.path.join(r_wav_path, '../'))
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elif r_audio_format == 'wav' and r_recog_type != 'wav':
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# datasets with waveform files
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r_wav_path = os.path.abspath(os.path.join(r_wav_path, '../../'))
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return r_recog_type, r_audio_format, r_wav_path
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def get_sr_from_bytes(wav: bytes):
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sr = None
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data = wav
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if len(data) > 44:
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try:
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header_fields = {}
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header_fields['ChunkID'] = str(data[0:4], 'UTF-8')
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header_fields['Format'] = str(data[8:12], 'UTF-8')
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header_fields['Subchunk1ID'] = str(data[12:16], 'UTF-8')
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if header_fields['ChunkID'] == 'RIFF' and header_fields[
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'Format'] == 'WAVE' and header_fields[
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'Subchunk1ID'] == 'fmt ':
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header_fields['SampleRate'] = struct.unpack('<I',
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data[24:28])[0]
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sr = header_fields['SampleRate']
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except Exception:
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# no treatment
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pass
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else:
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logger.warn('audio bytes is ' + str(len(data)) + ' is invalid.')
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return sr
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def get_sr_from_wav(fname: str):
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fs = None
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if os.path.isfile(fname):
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audio_type = os.path.basename(fname).lower()
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for support_audio_type in SUPPORT_AUDIO_TYPE_SETS:
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if audio_type.rfind(".{}".format(support_audio_type)) >= 0:
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if support_audio_type == "pcm":
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fs = None
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else:
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try:
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audio, fs = torchaudio.load(fname)
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except:
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audio, fs = librosa.load(fname)
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break
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if audio_type.rfind(".scp") >= 0:
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with open(fname, encoding="utf-8") as f:
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for line in f:
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wav_path = line.split()[1]
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fs = get_sr_from_wav(wav_path)
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if fs is not None:
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break
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return fs
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elif os.path.isdir(fname):
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dir_files = os.listdir(fname)
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for file in dir_files:
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file_path = os.path.join(fname, file)
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if os.path.isfile(file_path):
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fs = get_sr_from_wav(file_path)
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elif os.path.isdir(file_path):
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fs = get_sr_from_wav(file_path)
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if fs is not None:
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break
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return fs
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def find_file_by_ends(dir_path: str, ends: str):
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dir_files = os.listdir(dir_path)
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for file in dir_files:
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file_path = os.path.join(dir_path, file)
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if os.path.isfile(file_path):
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if ends == ".wav" or ends == ".WAV":
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audio_type = os.path.basename(file_path).lower()
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for support_audio_type in SUPPORT_AUDIO_TYPE_SETS:
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if audio_type.rfind(".{}".format(support_audio_type)) >= 0:
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return True
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raise NotImplementedError(
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f'Not supported audio type: {audio_type}')
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elif file_path.endswith(ends):
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return True
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elif os.path.isdir(file_path):
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if find_file_by_ends(file_path, ends):
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return True
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return False
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def recursion_dir_all_wav(wav_list, dir_path: str) -> List[str]:
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dir_files = os.listdir(dir_path)
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for file in dir_files:
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file_path = os.path.join(dir_path, file)
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if os.path.isfile(file_path):
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audio_type = os.path.basename(file_path).lower()
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for support_audio_type in SUPPORT_AUDIO_TYPE_SETS:
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if audio_type.rfind(".{}".format(support_audio_type)) >= 0:
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wav_list.append(file_path)
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elif os.path.isdir(file_path):
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recursion_dir_all_wav(wav_list, file_path)
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return wav_list
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def compute_wer(hyp_list: List[Any],
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ref_list: List[Any],
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lang: str = None) -> Dict[str, Any]:
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assert len(hyp_list) > 0, 'hyp list is empty'
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assert len(ref_list) > 0, 'ref list is empty'
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rst = {
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'Wrd': 0,
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'Corr': 0,
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'Ins': 0,
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'Del': 0,
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'Sub': 0,
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'Snt': 0,
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'Err': 0.0,
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'S.Err': 0.0,
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'wrong_words': 0,
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'wrong_sentences': 0
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}
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if lang is None:
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lang = global_asr_language
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for h_item in hyp_list:
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for r_item in ref_list:
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if h_item['key'] == r_item['key']:
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out_item = compute_wer_by_line(h_item['value'],
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r_item['value'],
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lang)
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rst['Wrd'] += out_item['nwords']
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rst['Corr'] += out_item['cor']
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rst['wrong_words'] += out_item['wrong']
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rst['Ins'] += out_item['ins']
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rst['Del'] += out_item['del']
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rst['Sub'] += out_item['sub']
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rst['Snt'] += 1
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if out_item['wrong'] > 0:
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rst['wrong_sentences'] += 1
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print_wrong_sentence(key=h_item['key'],
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hyp=h_item['value'],
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ref=r_item['value'])
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else:
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print_correct_sentence(key=h_item['key'],
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hyp=h_item['value'],
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ref=r_item['value'])
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break
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if rst['Wrd'] > 0:
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rst['Err'] = round(rst['wrong_words'] * 100 / rst['Wrd'], 2)
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if rst['Snt'] > 0:
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rst['S.Err'] = round(rst['wrong_sentences'] * 100 / rst['Snt'], 2)
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return rst
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def compute_wer_by_line(hyp: List[str],
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ref: List[str],
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lang: str = 'zh-cn') -> Dict[str, Any]:
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if lang != 'zh-cn':
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hyp = hyp.split()
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ref = ref.split()
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hyp = list(map(lambda x: x.lower(), hyp))
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ref = list(map(lambda x: x.lower(), ref))
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len_hyp = len(hyp)
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len_ref = len(ref)
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cost_matrix = np.zeros((len_hyp + 1, len_ref + 1), dtype=np.int16)
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ops_matrix = np.zeros((len_hyp + 1, len_ref + 1), dtype=np.int8)
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for i in range(len_hyp + 1):
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cost_matrix[i][0] = i
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for j in range(len_ref + 1):
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cost_matrix[0][j] = j
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for i in range(1, len_hyp + 1):
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for j in range(1, len_ref + 1):
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if hyp[i - 1] == ref[j - 1]:
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cost_matrix[i][j] = cost_matrix[i - 1][j - 1]
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else:
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substitution = cost_matrix[i - 1][j - 1] + 1
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insertion = cost_matrix[i - 1][j] + 1
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deletion = cost_matrix[i][j - 1] + 1
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compare_val = [substitution, insertion, deletion]
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min_val = min(compare_val)
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operation_idx = compare_val.index(min_val) + 1
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cost_matrix[i][j] = min_val
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ops_matrix[i][j] = operation_idx
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match_idx = []
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i = len_hyp
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j = len_ref
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rst = {
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'nwords': len_ref,
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'cor': 0,
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'wrong': 0,
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'ins': 0,
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'del': 0,
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'sub': 0
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}
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while i >= 0 or j >= 0:
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i_idx = max(0, i)
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j_idx = max(0, j)
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if ops_matrix[i_idx][j_idx] == 0: # correct
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if i - 1 >= 0 and j - 1 >= 0:
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match_idx.append((j - 1, i - 1))
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rst['cor'] += 1
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i -= 1
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j -= 1
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elif ops_matrix[i_idx][j_idx] == 2: # insert
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i -= 1
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rst['ins'] += 1
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elif ops_matrix[i_idx][j_idx] == 3: # delete
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j -= 1
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rst['del'] += 1
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elif ops_matrix[i_idx][j_idx] == 1: # substitute
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i -= 1
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j -= 1
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rst['sub'] += 1
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if i < 0 and j >= 0:
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rst['del'] += 1
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elif j < 0 and i >= 0:
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rst['ins'] += 1
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match_idx.reverse()
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wrong_cnt = cost_matrix[len_hyp][len_ref]
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rst['wrong'] = wrong_cnt
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return rst
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def print_wrong_sentence(key: str, hyp: str, ref: str):
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space = len(key)
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print(key + yellow_color + ' ref: ' + ref)
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print(' ' * space + red_color + ' hyp: ' + hyp + end_color)
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def print_correct_sentence(key: str, hyp: str, ref: str):
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space = len(key)
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print(key + yellow_color + ' ref: ' + ref)
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print(' ' * space + green_color + ' hyp: ' + hyp + end_color)
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def print_progress(percent):
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if percent > 1:
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percent = 1
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res = int(50 * percent) * '#'
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print('\r[%-50s] %d%%' % (res, int(100 * percent)), end='')
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