How to Build a Speech Synthesizer with OpenAI GPT-3 and Google Text-to-Speech API

Posted on by Panther

In this tutorial, we will guide you through the process of building a speech synthesizer using OpenAI GPT-3 and the Google Text-to-Speech (TTS) API. By combining the power of GPT-3’s natural language processing capabilities with Google’s TTS engine, you can create a speech synthesizer that can convert any text into spoken words.

Prerequisites

To follow along with this tutorial, you will need:

  1. OpenAI GPT-3 API access: You will need to sign up and obtain API access from OpenAI to use GPT-3. Visit the OpenAI website to get started.

  2. Google Cloud Platform (GCP) account: You will need a GCP account to use the Google TTS API. If you don’t have an account, sign up for a free trial on the GCP website.

  3. Python 3: Make sure you have Python 3 installed on your system.

  4. Python libraries: Install the following Python libraries using pip:

    pip install openai google-cloud-texttospeech

Step 1: Set up Google TTS API

  1. Enable the Google TTS API: Go to the Google Cloud Console, enable the Text-to-Speech API, and create a new project or use an existing one.

  2. Generate API credentials: Generate an API key for the Text-to-Speech API. Follow the instructions provided by Google to create a service account key. Download the JSON key file and remember the path where you saved it.

  3. Set the environment variable: Set the path to the JSON key file as an environment variable named GOOGLE_APPLICATION_CREDENTIALS. This will allow the Google Cloud client library to find the credentials when making API requests.

    export GOOGLE_APPLICATION_CREDENTIALS=/path/to/keyfile.json

Step 2: Set up OpenAI GPT-3

  1. Get GPT-3 API access: Sign up for GPT-3 API access on the OpenAI website. Follow the instructions provided by OpenAI to get your API key.

  2. Set the API key: Set your OpenAI GPT-3 API key as an environment variable named OPENAI_API_KEY.

    export OPENAI_API_KEY=your_api_key_here

Step 3: Writing the Speech Synthesizer Script

Now that we have the necessary API keys and environment variables set up, let’s start writing the Python script that will perform the actual speech synthesis.

import openai
from google.cloud import texttospeech

openai.api_key = os.getenv("OPENAI_API_KEY")
client = texttospeech.TextToSpeechClient()

def synthesize_text_with_gpt3(text):
    response = openai.Completion.create(
        engine="davinci",
        prompt=text,
        max_tokens=200,
        n=1,
        stop=None,
        temperature=0.7
    )
    synthesized_text = response.choices[0].text.strip()
    return synthesized_text

def synthesize_speech_with_tts(text):
    input_text = texttospeech.SynthesisInput(text=text)
    voice = texttospeech.VoiceSelectionParams(
        language_code="en-US",
        ssml_gender=texttospeech.SsmlVoiceGender.NEUTRAL
    )
    audio_config = texttospeech.AudioConfig(
        audio_encoding=texttospeech.AudioEncoding.MP3
    )
    response = client.synthesize_speech(
        input=input_text,
        voice=voice,
        audio_config=audio_config
    )
    return response.audio_content

def synthesize_speech(text):
    gpt3_output = synthesize_text_with_gpt3(text)
    speech_output = synthesize_speech_with_tts(gpt3_output)
    return speech_output

input_text = """Hello, how are you today?"""
speech_output = synthesize_speech(input_text)

with open("output.mp3", "wb") as f:
    f.write(speech_output)

This script uses two separate functions: synthesize_text_with_gpt3 to generate natural language responses using GPT-3, and synthesize_speech_with_tts to convert the generated text into speech using the Google TTS API. The synthesize_speech function combines both functions and returns the synthesized speech as raw audio data.

Replace your_api_key_here in the script with your actual OpenAI GPT-3 API key.

Step 4: Running the Speech Synthesizer

  1. Save the script to a file named speech_synthesizer.py.

  2. Run the script:

    python speech_synthesizer.py
  3. The script will generate an MP3 file named output.mp3 containing the synthesized speech. You can play the file using any media player.

Customizing the Speech Synthesis

You can customize the speech synthesis by adjusting the parameters in the script:

  • max_tokens (in synthesize_text_with_gpt3): Controls the maximum number of tokens to generate from GPT-3. A larger value generates more verbose responses.

  • temperature (in synthesize_text_with_gpt3): Controls the randomness of the generated text. A higher value (e.g. 1.0) produces more random outputs, while a lower value (e.g. 0.1) produces more focused and deterministic outputs.

  • language_code (in synthesize_speech_with_tts): Sets the language of the synthesized speech. Change it to match the desired language code, e.g., en-US for English (United States).

You can experiment with different combinations of these parameters to achieve the desired speech synthesis output.

Conclusion

In this tutorial, you learned how to build a speech synthesizer using OpenAI GPT-3 and the Google Text-to-Speech API. By combining the natural language processing capabilities of GPT-3 with Google’s powerful TTS engine, you can generate high-quality synthesized speech from any text input. Experiment with different prompts and parameters to create unique and customized speech synthesis applications.

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