Building an AI Voice Assistant: Speech Recognition to Response

from gtts import gTTS
import pygame

def speak(text, lang='en'):
    tts = gTTS(text=text, lang=lang)
    tts.save('response.mp3')
    
    pygame.mixer.init()
    pygame.mixer.music.load('response.mp3')
    pygame.mixer.music.play()
    while pygame.mixer.music.get_busy():
        continue

Multilingual Support

For Arabic or French voice assistants:

• STT: Whisper supports 100+ languages
• NLU: GPT-4 works in Arabic and French
• TTS: Google TTS supports Arabic and French

Real-World Use Case: Medical Assistant

A health tech startup in Casablanca built a Darija-speaking voice assistant for:

• Appointment scheduling
• Medication reminders
• Symptom triage
• Health information

The assistant handles 1,000+ calls daily in Moroccan Arabic.

Deployment

• Use WebSocket for real-time communication
• Deploy STT on GPU instances for low latency
• Cache common responses for speed
• Monitor accuracy and user satisfaction

Next Steps

• Add wake word detection ("Hey Assistant")
• Implement multi-turn conversations
• Add custom actions (send email, control smart home)
• Support code-switching between languages