Notes

import tkinter as tk
import speech_recognition as sr
from keras.models import load_model
import numpy as np
import joblib

# Create tkinter window
root = tk.Tk()
root.title("Emoji Feedback")

# Load the scaler
scaler = joblib.load('your_scaler.pkl')

# Load the trained model
model = joblib.load('your_model.pkl')

# Define emotion labels
emotion_labels = {
0: 'neutral',
1: 'calm',
2: 'happy',
3: 'sad',
4: 'angry',
5: 'fear',
6: 'disgust',
7: 'surprise'
}

# Define emojis
emojis = {
'neutral': "😐",
'calm': "😌",
'happy': "😄",
'sad': "😢",
'angry': "😡",
'fear': "😨",
'disgust': "🤢",
'surprise': "😯"
}

# Function to handle button click event
def predict_emotion():
user_input = input_entry.get()
if user_input.strip() == "":
predict_emotion_from_voice()
else:
features = preprocess_input(user_input)
make_prediction(features)

# Function to handle voice input
def predict_emotion_from_voice():
recognizer = sr.Recognizer()
with sr.Microphone() as source:
print("Listening...")
audio = recognizer.listen(source)
print("Processing...")
try:
user_input = recognizer.recognize_google(audio)
input_entry.delete(0, tk.END)
input_entry.insert(0, user_input)
features = preprocess_input(user_input)
make_prediction(features)
except sr.UnknownValueError:
print("Google Speech Recognition could not understand audio")
except sr.RequestError as e:
print("Could not request results from Google Speech Recognition service; {0}".format(e))

# Function to preprocess input
def preprocess_input(input_text):
# Here, you should perform your feature extraction process
# Ensure that the features have the correct shape and format

# Example: Dummy feature extraction for demonstration
features = [[len(input_text)]] # Replace this with your actual feature extraction process

return features

# Function to make prediction
def make_prediction(features):
# Scale the features using the scaler
scaled_features = scaler.transform(features)

# Make prediction using the model
prediction = model.predict(scaled_features)

# Get the predicted emotion label
predicted_emotion = np.argmax(prediction)
predicted_emotion_label = emotion_labels[predicted_emotion]

# Update the emoji label with the corresponding emoji
emoji_label.configure(text=emojis[predicted_emotion_label])

# Create and place input elements
input_label = tk.Label(root, text="Enter text (or press button for voice input):")
input_label.pack()

input_entry = tk.Entry(root)
input_entry.pack()

# Create and place predict button
predict_button = tk.Button(root, text="Predict", command=predict_emotion)
predict_button.pack()

# Create and place emoji label
emoji_label = tk.Label(root, font=("Segoe UI Emoji", 50))
emoji_label.pack()

# Run the tkinter event loop
root.mainloop()