Audio Screen Blackout

What is it?

Audio Screen Blackout is a productivity-focused tool designed for workplace environments. It monitors the audio levels of individuals during meetings or collaborative work sessions and blacks out the screen of anyone speaking too loudly. This encourages a more professional and focused atmosphere by helping to minimize distraction.

How it works?

FORMAT = pyaudio.paInt16:

FORMAT specifies the audio format or data type of the samples in the audio stream. In this case, it's set to pyaudio.paInt16, which indicates that each audio sample is represented as a 16-bit signed integer. This format is common for uncompressed PCM audio.

pyaudio.paInt16 is a constant provided by the PyAudio library, which corresponds to 16-bit signed integer audio format.

Audio samples are typically represented as integers (like pyaudio.paInt16) or floating-point numbers, and the choice of format affects the range and precision of the audio data.

CHANNELS = 1:

CHANNELS specifies the number of audio channels in the audio stream. In this case, it's set to 1, indicating a mono audio stream.

In mono audio, there is a single audio channel, and the audio is represented as a single stream of data. In stereo audio, for example, there would be two channels, typically representing the left and right audio channels separately.

RATE = 44100:

RATE specifies the sample rate or sampling frequency of the audio stream. It defines how many audio samples are captured or played back per second.

In this case, RATE is set to 44100, which means the audio stream has a sample rate of 44,100 samples per second. This is a standard sample rate used for CD-quality audio.

The sample rate determines the frequency range that the audio stream can capture or reproduce. In audio processing, it's important to match the sample rate of your audio data with the expected sample rate of your audio equipment.

CHUNK = 1024:

CHUNK specifies the buffer size for audio data. It defines how many audio samples are processed at a time during each read or write operation.

In this case, CHUNK is set to 1024, indicating that 1024 audio samples are read or written at once. The choice of buffer size can affect the performance and latency of audio processing.

Smaller chunk sizes can lead to lower latency but may require more frequent data processing. Larger chunk sizes may reduce the processing overhead but introduce higher latency.

Relation between CHUNK (buffer size) and RATE (same rate)

1. Sample Rate (RATE): This defines how many audio samples are captured or played back per second. It sets the rate at which new audio data is generated or received.

2. Buffer Size (CHUNK): This specifies how many audio samples are processed at a time during each read or write operation. It determines the size of the "chunks" of audio data that your program works with at a time.

   • A smaller CHUNK size can lead to lower latency because your program processes smaller portions of audio more frequently. However, it may require more CPU resources.

   • A larger CHUNK size can reduce the processing overhead because you're processing larger portions of audio at once, but it may introduce higher latency.

Now, the buffer size (in terms of the number of samples) at a given sample rate is:

Buffer Size (samples) is calculated as the ratio of RATE to CHUNK:

Buffer Size (samples) = RATE / CHUNK

For example, if your RATE is 44,100 samples per second, and your CHUNK is 1024 samples:

Buffer Size (samples) is calculated as:

Buffer Size (samples) = 44,100 / 1024 ≈ 43.07

This means that approximately every 43 milliseconds (or 0.043 seconds), the buffer will be filled with new audio data, and your program will process this data. If your program's processing speed cannot keep up with this rate, it can lead to issues like audio dropouts or degraded performance, but it doesn't necessarily cause a crash.