Speech Recognition on Brainy Pi: A Developer’s Guide

Introduction

In recent years, voice interfaces have become increasingly popular, allowing users to interact with devices using natural language. One essential component of voice interfaces is speech-to-text conversion, which enables the translation of spoken words into written text. In this blog post, we’ll explore how to implement a speech-to-text converter on a Brainy Pi using Python and a microphone. This guide is for developers with a basic understanding of Python to implement Speech Recognition on Brainy Pi .

Prerequisites

Before we begin, ensure you have the following:

• A Brainy Pi Dev Board

• A USB microphone

• An Internet connection

• Basic knowledge of Python and Brainy Pi

Setting Up the Environment

To start, we need to set up our Brainy Pi environment. Follow these steps:

1. Connect a compatible USB microphone to your Brainy Pi.

2. Open a terminal or SSH into your Brainy Pi.

3. Now, update the package list by running the following command:

   sudo apt-get update

4. Install the necessary dependencies by executing the following commands:

   sudo apt-get install portaudio19-dev python3-dev flac
   pip install SpeechRecognition
   pip install Pyaudio

Implementation Steps

Now that we have our environment ready, let’s implement the speech-to-text converter on the Raspberry Pi using Python:

1. Open your favorite text editor and create a new Python script. Let’s call it speech_to_text.py.

2. So, let’s Import the SpeechRecognition library,  for speech recognition in Python.

   import speech_recognition as sr

3. Create a recognizer object to recognize speech.

   r = sr.Recognizer()

4. After object is initialized then get the list of available microphones on the system, using the list_microphone_names() method.

   mic_list = sr.Microphone.list_microphone_names()

5. Iterate through the list of microphones, and look for the USB mic. Set the device_id variable to its index in the mic_list.

   mic_name = "USB PnP Sound Device: Audio (hw:2,0)"
   for i, microphone_name in enumerate(mic_list):
       if microphone_name == mic_name:
           device_id = i

6. Now lets capture audio input from the selected microphone and store it in the audio variable.

   with sr.Microphone(device_index=device_id) as source:
       print("Say something...")
       r.adjust_for_ambient_noise(source, duration=0.2)
       audio = r.listen(source)

7. Convert the captured audio to text using the Google Speech Recognition API.

   try:
       text = r.recognize_google(audio)
       print("You said:", text)
   except sr.UnknownValueError:
       print("Speech recognition could not understand audio.")
   except sr.RequestError as e:
       print("Could not request results from Speech Recognition service; {0}".format(e))

8. To handle errors, we add exception handling to catch any unknown value errors and request errors that may occur. This will ensure that our program does not crash in case of unexpected errors.

9. Finally, we print out the text recognized text by the Google Speech Recognition API.

10. Then save the script and exit the text editor.

Final Code for Speech Recognition on Brainy Pi

Here is the complete code for speech_to_text.py:

import speech_recognition as sr

# Create a recognizer object
r = sr.Recognizer()

mic_list = sr.Microphone.list_microphone_names()

# Select the USB microphone by name
mic_name = "USB PnP Sound Device: Audio (hw:2,0)"
device_id = next((i for i, microphone_name in enumerate(mic_list) if microphone_name == mic_name), None)

# Check if the selected microphone was found
if device_id is None:
    print("Could not find the selected microphone. Available microphones:")
    print(mic_list)
    exit()

# Start listening to the microphone
with sr.Microphone(device_index=device_id) as source:
    print("Say something...")
    # Adjust the recognizer's sensitivity to ambient noise
    r.adjust_for_ambient_noise(source, duration=0.2)
    audio = r.listen(source)

    # Convert speech to text
    try:
        text = r.recognize_google(audio)
        print("You said:", text)
    except sr.UnknownValueError:
        print("Could not understand audio")
    except sr.RequestError as e:
        print("Could not request results from Speech Recognition service; {0}".format(e))

Running the code

python3 speech_to_text.py

Once program runs, say something in the microphone the code will covert speech to text and print the output.

Conclusion

In this blog post, we’ve seen how to implement speech recognition on a Brainy Pi using Python and the SpeechRecognition library. We’ve covered the required steps for setting up the environment, selecting the USB microphone, capturing audio input, and converting the speech to text using Google’s Speech Recognition API. We’ve also added exception handling to handle any errors that may occur during the speech recognition process.

The possibilities of using speech recognition on a Brainy Pi are endless. You can use it to create voice-controlled home automation systems, voice-based assistants, or any other project that requires natural language processing. With the SpeechRecognition library, the process is relatively straightforward, and the API is intuitive and easy to use.

We hope this blog post has helped you get started with speech recognition on your Brainy Pi. Happy coding!