Building a Simple Voice Recognition Application

Intermediate

🎤 Let's Walk Through Creating a Basic Voice Recognition App Using Python and Google Cloud Speech-to-Text API

✅ Prerequisites

  • Google Cloud account and project
  • Enable Speech-to-Text API
  • Service account credentials (.json file)

🪜 Steps

1. Install necessary libraries:

pip install google-cloud-speech
  1. Configure credentials:
import os
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "path/to/your/credentials.json"
  1. Write the recognition code:
from google.cloud import speech

def transcribe_speech(audio_content):
    client = speech.SpeechClient()
    audio = speech.RecognitionAudio(content=audio_content)
    config = speech.RecognitionConfig(
        encoding=speech.RecognitionConfig.AudioEncoding.LINEAR16,
        sample_rate_hertz=16000,
        language_code="en-US",
    )
    response = client.recognize(config=config, audio=audio)
    for result in response.results:
        print(f"Transcription: {result.alternatives[0].transcript}")

# Load audio file
with open('audio.wav', 'rb') as audio_file:
    audio_content = audio_file.read()

transcribe_speech(audio_content)

This example demonstrates how to transcribe pre-recorded audio. For real-time processing, consider using streaming recognition APIs. Remember to handle API quotas and errors appropriately. This basic application lays the foundation for more complex voice-enabled systems.