Speech To Text using ESP32
Science & Technology
Introduction
In this guide, we will explore how to convert speech into text using the ESP32 board and Google Cloud services. This project lays the foundational work for creating a standalone Voice Assistant using ChatGPT, allowing a microphone to capture voice commands and a speaker to provide audible responses.
Introduction
The ESP32 is a versatile microcontroller that supports Wi-Fi and Bluetooth operations, making it ideal for IoT applications. This project focuses on implementing speech-to-text conversion, essential for voice-controlled applications. The Google Cloud Speech-to-Text API allows us to transcribe spoken words accurately into text format.
Set Up Google Cloud Account
To use the Google Cloud Speech-to-Text services, you first need an account and an API key. Follow these steps:
- Visit Google Cloud's Speech-to-Text page.
- Log in with your Google account.
- Click on "Start Free" to create an account, which provides a $ 300 credit valid for 90 days.
- Fill in the required information, including your organization type and billing data (card information is needed for verification but will not charge until you exceed the free credits).
- Navigate to the "APIs & Services" section to enable the Speech-to-Text API.
- Create credentials by generating an API key, which you'll use in your Arduino code. Make sure to restrict this key to the Speech-to-Text API for security purposes.
Hardware Requirements
The following hardware components are used in this project:
- ESP32 Development Board: The microcontroller that runs our code.
- MEMS Microphone: Captures audio input.
- Audio Output Device (Speaker): Plays back responses.
Arduino Code Overview
Below is a high-level overview of the code structure for converting speech to text.
- Microphone Input: The microphone captures audio data, storing it in a 16-bit linear format.
- API Call to Google Cloud: The audio data is sent to the Google Cloud API as a HTTP POST request with the necessary configuration in JSON format.
- Audio Configuration: This includes encoding type (linear 16), sample rate (16000 Hz), and language code (such as 'en-IN' for Indian English).
- Response Handling: The response from Google Cloud includes the transcribed text and confidence level, indicating transcription accuracy.
Code Upload
To upload the code:
- Open the Arduino IDE and ensure you have the correct ESP32 board package. You might need to downgrade to version 1.0.6 to avoid compilation errors.
- Change Wi-Fi credentials and the API key in the code.
- Upload the code while ensuring the ESP32 is connected via the correct COM port.
- Use the Serial Monitor to observe the output. The system will indicate when recording starts and ends, displaying the recognized text afterward.
Conclusion
With this setup, you can convert speech into text using the ESP32 and Google Cloud services. This capability is essential for building voice-responsive applications, paving the way for the upcoming ChatGPT-based voice assistant project.
Keywords
- ESP32
- Speech-to-Text
- Google Cloud
- API Key
- Arduino
- MEMS Microphone
- JSON Format
FAQ
Q1: What are the basic requirements to set up Speech-to-Text on ESP32?
A1: You need an ESP32 development board, a MEMS microphone, a speaker, and a Google Cloud account with access to the Speech-to-Text API.
Q2: How does one generate an API key for Google Cloud Speech-to-Text service?
A2: After creating a Google Cloud account, navigate to APIs & Services. Enable the Speech-to-Text API and create an API key in the credentials section.
Q3: Can the microphone record audio for more than 3 seconds?
A3: The current implementation is limited to about 2.5 to 3 seconds. Extending this duration may lead to errors, but optimizations can be explored.
Q4: How do I restrict the API key for security?
A4: You can restrict the API key's usage in the Google Cloud console, limiting it to only the Speech-to-Text API.
Q5: What language codes can I use with the Speech-to-Text API?
A5: You can use various language codes available in the Google documentation, such as 'en-IN' for Indian English or others depending on your requirements.
