In this tutorial, we will guide you on how to build a Speech-to-Text app using OpenAI GPT-3 and the Google Speech API. By the end of this tutorial, you will have a working app that can convert spoken language into written text.
Prerequisites
Before we begin, make sure you have the following prerequisites:
- OpenAI GPT-3 API key: You will need an API key to access the GPT-3 API. If you don’t have an API key, you can apply for one on the OpenAI website.
-
Google Speech API credentials: You will need a service account key file to authenticate your requests to the Google Speech API. You can get this file by creating a new service account on the Google Cloud Platform console.
-
Python and pip: Make sure you have Python installed on your machine, along with pip (the Python package installer).
Step 1: Set Up the Project
Let’s start by creating a new directory for our project and setting up a virtual environment. Open your terminal and run the following commands:
mkdir speech-to-text-app
cd speech-to-text-app
python -m venv env
source env/bin/activate # for macOS and Linux
envScriptsactivate # for Windows
Next, let’s install the required Python packages:
pip install openai google-cloud-speech
Step 2: Authenticate with the Google Speech API
To authenticate with the Google Speech API, you will need to create a service account key file in the Google Cloud Platform console. Here’s how you can do it:
- Go to the Google Cloud Platform console.
-
Create a new project or select an existing project.
-
Go to the “IAM & Admin” section.
-
Click on “Service Accounts,” then “Create Service Account.”
-
Give your service account a name and a description, and click on “Create.”
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In the “Service Account Permissions” section, select the roles you want to assign to the service account (e.g., “Speech-to-Text Admin”).
-
In the “Keys” section, click on “Add Key,” then select “Create new key.” Choose the JSON key type and click on “Create.”
-
Save the generated JSON key file to a secure location.
Now that you have the service account key file, let’s authenticate our application with the Google Speech API using this file. Create a new Python script called google_speech_auth.py
and add the following code:
import os
from google.cloud import speech_v1p1beta1 as speech
def authenticate():
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "path/to/your/keyfile.json"
client = speech.SpeechClient()
return client
Make sure to replace "path/to/your/keyfile.json"
with the actual file path of your service account key file.
Step 3: Convert Speech to Text with the Google Speech API
Now that we are authenticated with the Google Speech API, let’s write a function that uses the API to convert speech to text. Create a new Python script called google_speech.py
and add the following code:
from google.cloud.speech_v1p1beta1.types import RecognitionConfig, RecognitionAudio
def speech_to_text(client, audio_file):
with open(audio_file, "rb") as audio:
content = audio.read()
audio = RecognitionAudio(content=content)
config = RecognitionConfig(
encoding=RecognitionConfig.AudioEncoding.LINEAR16,
sample_rate_hertz=16000,
language_code="en-US",
)
response = client.recognize(config=config, audio=audio)
text = ""
for result in response.results:
text += result.alternatives[0].transcript
return text
This function takes the authenticated client object and the path to the audio file as input. It reads the audio file, creates the necessary objects for the API request, and sends the request to the API. Finally, it extracts the transcribed text from the API response and returns it.
Step 4: Generate Text with OpenAI GPT-3
Now that we can convert speech to text using the Google Speech API, let’s generate text using OpenAI GPT-3. Create a new Python script called openai_gpt3.py
and add the following code:
import openai
def generate_text(api_key, prompt):
openai.api_key = api_key
response = openai.Completion.create(
engine="text-davinci-003",
prompt=prompt,
max_tokens=100,
)
return response.choices[0].text.strip()
This function takes the GPT-3 API key and the prompt text as input. It sets the API key, creates a completion using the GPT-3 engine, and sends the prompt to the API. Finally, it extracts the generated text from the API response and returns it.
Step 5: Putting It All Together
Now that we have the components ready, let’s create our final script that combines the speech-to-text functionality with the text generation capability. Create a new Python script called speech_to_text_app.py
and add the following code:
from google_speech_auth import authenticate
from google_speech import speech_to_text
from openai_gpt3 import generate_text
def main():
client = authenticate()
audio_file = "path/to/your/audio/file.wav" # Replace with your audio file
text = speech_to_text(client, audio_file)
generated_text = generate_text("your-gpt3-api-key", text) # Replace with your GPT-3 API key
print(generated_text)
if __name__ == "__main__":
main()
Make sure to replace "path/to/your/audio/file.wav"
with the actual path to your audio file, and "your-gpt3-api-key"
with your GPT-3 API key.
Step 6: Run the Speech-to-Text App
Finally, let’s run our Speech-to-Text app and see the magic happen! Make sure you have a valid audio file in the specified location and run the following command in your terminal:
python speech_to_text_app.py
The app will first convert the speech in the audio file to text using the Google Speech API. It will then generate additional text based on the transcribed speech using OpenAI GPT-3. The generated text will be printed in the console.
Feel free to modify the speech_to_text_app.py
script based on your needs. You can use different audio files, change the GPT-3 prompt, or extend the functionality as desired.
Conclusion
In this tutorial, we have learned how to build a Speech-to-Text app using OpenAI GPT-3 and the Google Speech API. We have covered the steps to authenticate with the Google Speech API, convert speech to text, generate text with GPT-3, and put everything together in a working app. You can now apply these concepts to build your own speech-related applications with these powerful AI technologies.