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| # Copyright (c) 2020 Mobvoi Inc (Binbin Zhang) | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| import json | |
| import math | |
| import numpy as np | |
| def _load_json_cmvn(json_cmvn_file): | |
| """ Load the json format cmvn stats file and calculate cmvn | |
| Args: | |
| json_cmvn_file: cmvn stats file in json format | |
| Returns: | |
| a numpy array of [means, vars] | |
| """ | |
| with open(json_cmvn_file) as f: | |
| cmvn_stats = json.load(f) | |
| means = cmvn_stats['mean_stat'] | |
| variance = cmvn_stats['var_stat'] | |
| count = cmvn_stats['frame_num'] | |
| for i in range(len(means)): | |
| means[i] /= count | |
| variance[i] = variance[i] / count - means[i] * means[i] | |
| if variance[i] < 1.0e-20: | |
| variance[i] = 1.0e-20 | |
| variance[i] = 1.0 / math.sqrt(variance[i]) | |
| cmvn = np.array([means, variance]) | |
| return cmvn | |
| def _load_kaldi_cmvn(kaldi_cmvn_file): | |
| """ Load the kaldi format cmvn stats file and calculate cmvn | |
| Args: | |
| kaldi_cmvn_file: kaldi text style global cmvn file, which | |
| is generated by: | |
| compute-cmvn-stats --binary=false scp:feats.scp global_cmvn | |
| Returns: | |
| a numpy array of [means, vars] | |
| """ | |
| means = [] | |
| variance = [] | |
| with open(kaldi_cmvn_file, 'r') as fid: | |
| # kaldi binary file start with '\0B' | |
| if fid.read(2) == '\0B': | |
| logging.error('kaldi cmvn binary file is not supported, please ' | |
| 'recompute it by: compute-cmvn-stats --binary=false ' | |
| ' scp:feats.scp global_cmvn') | |
| sys.exit(1) | |
| fid.seek(0) | |
| arr = fid.read().split() | |
| assert (arr[0] == '[') | |
| assert (arr[-2] == '0') | |
| assert (arr[-1] == ']') | |
| feat_dim = int((len(arr) - 2 - 2) / 2) | |
| for i in range(1, feat_dim + 1): | |
| means.append(float(arr[i])) | |
| count = float(arr[feat_dim + 1]) | |
| for i in range(feat_dim + 2, 2 * feat_dim + 2): | |
| variance.append(float(arr[i])) | |
| for i in range(len(means)): | |
| means[i] /= count | |
| variance[i] = variance[i] / count - means[i] * means[i] | |
| if variance[i] < 1.0e-20: | |
| variance[i] = 1.0e-20 | |
| variance[i] = 1.0 / math.sqrt(variance[i]) | |
| cmvn = np.array([means, variance]) | |
| return cmvn | |
| def load_cmvn(cmvn_file, is_json): | |
| if is_json: | |
| cmvn = _load_json_cmvn(cmvn_file) | |
| else: | |
| cmvn = _load_kaldi_cmvn(cmvn_file) | |
| return cmvn[0], cmvn[1] | |