How can I build a custom GPT using Whisper for speech-to-text and OpenAI TTS for text-to-speech?

Below is a high-level walkthrough of how you could build a Custom GPT that uses Whisper for speech-to-text and OpenAI’s TTS for text-to-speech via GPT Actions:

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1. Understand the Building Blocks

• Custom GPTs & GPT Actions:
  Custom GPTs let you tailor ChatGPT for specific tasks. GPT Actions within these Custom GPTs allow you to connect to external APIs. In your case, you’ll define two actions: one to convert speech (via Whisper) into text (speech-to-text) and another to convert chatbot responses back into speech (text-to-speech using OpenAI TTS).

• Speech-to-Text (Whisper):
  The Whisper model is designed to transcribe audio. You will integrate this as an API call that sends an audio file and receives text.

• Text-to-Speech (TTS):
  The OpenAI TTS API generates spoken audio from text. It supports multiple languages and turns processed text into natural-sounding speech.

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2. Setting Up Your Custom GPT

• Access the Custom GPT Dashboard:
  Log in to the OpenAI platform and navigate to the section for creating Custom GPTs. This is where you will configure your GPT Actions.

• Design Your Workflow:

  1. Audio Input:
     • The user speaks. Your client-side code sends the audio to your backend.
  2. Speech-to-Text Conversion:
     • Use an action that calls the Whisper API endpoint to transcribe the audio.
     • Define this action in your Custom GPT’s configuration with instructions to handle audio inputs and output text.
  3. ChatGPT Processing:
     • The text output from Whisper is fed into ChatGPT via your Custom GPT. This allows ChatGPT to understand the query or command.
  4. Text-to-Speech Conversion:
     • Once ChatGPT generates a response, send this text to the OpenAI TTS API using a second GPT Action.
     • Configure the action to call the TTS endpoint, converting text into spoken audio.

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3. Integrating API Calls with GPT Actions

• Action Definitions:
  In your Custom GPT configuration, define actions for each step using natural language instructions that map to API calls. For example:

  JSONCopied
  {
    "action": "speech_to_text",
    "description": "Convert an audio file to text using Whisper.",
    "parameters": {
      "audioFile": "<audio_file_reference>"
    }
  }

  And then for TTS:

  JSONCopied
  {
    "action": "text_to_speech",
    "description": "Convert text to spoken audio using OpenAI TTS.",
    "parameters": {
      "text": "<chatgpt_response_text>",
      "language": "en"  // or specify another supported language
    }
  }

• Function Calling:
  GPT Actions use a function calling mechanism where natural language commands are translated into JSON schema required for the API call. This means you define the structure (or schema) for your API calls in your Custom GPT setup, and ChatGPT will automatically generate the appropriate calls based on user input and context.

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4. Testing and Iteration

• Simulate the Workflow:
  • Start by testing each action individually (Whisper transcription and TTS generation) to ensure the API calls work as expected.
  • Integrate them into a complete end-to-end test: record or upload an audio clip, process it through Whisper, let ChatGPT handle the text, then convert the final response back into speech via TTS.
• Iterate & Optimize:
  • Fine-tune your action instructions based on test outcomes.
  • Adjust the natural language prompts so that ChatGPT reliably triggers the correct GPT Actions.

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5. Helpful Resources

• OpenAI Documentation:
  Refer to the GPT Actions documentation for detailed instructions on configuration and schema definitions.

• API References:
  Make sure you have access to the latest endpoints and parameter details for both Whisper (speech-to-text) and TTS (text-to-speech).

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This approach lets you leverage the natural language processing capabilities of ChatGPT along with APIs for audio transformation, effectively building a multi-modal Custom GPT. If you need further technical specifics (like endpoint URLs or detailed parameter types), consult OpenAI’s API documentation for Whisper and TTS.

Happy coding!