Speech Emotion Recogination
DataSet import os Root = "/content/drive/MyDrive/Colab_Notebooks/RAVDESS_Emotional_speech_audio" os.chdir ( Root ) ls modelForPrediction1.sav modelForPrediction.sav speech-emotion-recognition-ravdess-data / Speech_Emotion_Recognition_with_librosa.ipynb standardScalar.sav import librosa import soundfile import os , glob , pickle import numpy as np from sklearn.model_selection import train_test_split from sklearn.neural_network import MLPClassifier from sklearn.metrics import accuracy_score #Extract features (mfcc, chroma, mel) from a sound file def extract_feature ( file_name , mfcc , chroma , mel ) : with soundfile.SoundFile ( file_name ) as sound_file : X = sound_file.read ( dtype= "float32" ) ...
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