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import os
import time
from modules.emotion import Emotion
from modules.transcription import Transcription
transcription_model = "tiny.en"
emotion_model = "joeddav/distilbert-base-uncased-go-emotions-student"
transcription_obj = Transcription(model_name=transcription_model)
emotion_obj = Emotion(model_name=emotion_model)
class Module:
def predict(self, audio_path: str) -> str:
"""Loads audio, gets transcription and detects emotion
Args:
audio_path (str): path to the audio file
Returns:
str: emotion
"""
print("Getting transcription...")
start_time = time.time()
if text := transcription_obj.transcribe(audio_path=audio_path):
print("Text: ", text, time.time() - start_time)
start_time = time.time()
emotion = emotion_obj.detect_emotion(text=text)
print("Emotion: ", emotion, time.time() - start_time)
return text, emotion
return None
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