python实现说话人识别实验与开发
Auto Speaker Recognition main.py the main file for test audio_record.py record audio from micro phone count_days.py count days between two date. 20110805 20160903 mfcc_feature.py extract mfcc feature from wav files SGD.model* the trained model on train set , and the accurate is 70% util.py contains the most useful functions train train data is 75% of all the data test test data is 25% of all the data and has no overlap with train set classification_SGD.py is the main classification function py file , and it used the sklearn's SGD niter was set 10000 could get 70% of accurate. classification_BNB.py this is the sklern naive_bayes BernoulliNB , and it reach to just 56% classification_DT.py this is the sklern tree.DecisionTreeClassifier , and it reach to just 63% classification_GB.py this is the sklern GradientBoostingClassifier, and it reach to the best now of 76% when n_estimators=1000, but it produce too many model components to store. classification_GNB.py this is the sklern naive_bayes GaussianNB, and it reach to just 63% vote_result.py add a vote decsion , every method have the acurrcy number ticiks to vote the final answer. after the vote , we achived 96% at test set. beta1.0
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- 岁月风尘仆2020-07-31不咋地,差评,
- mjx13145202018-07-26还可以,感觉不错
- JohnsonYu2019-02-21这是啥玩意?404页面哈
- haierqian2017-10-30这是啥玩意?404页面哈
- 无水先生2021-12-01一般一般地。
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