Research Article
Deep Learning-Based Classification of Spoken English Digits
Algorithm 1
The Random Forest Classification Model.
| (1) | procedure RandomForest Classifier () (⊳) contains the STFT features of each audio sample, while contains the target audio class label | | (2) | Read the dataset using the library “Librosa” | | (3) | Extract STFT features from the audio | | (4) | One hot encode the audio data to produce the class label. | | (5) | Split the dataset into training and testing set with STFT features as the input and audio class as the target label | | (6) | Start the random forest model | | (7) | Set up the hyperparameters tuning: n_estimators, max_depth | | (8) | RandomForestClassifier (Hyperparameters) | | (9) | Fitting training and the testing dataset | | (10) | Evaluate the model | | (11) | end procedure |
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