docs(readme): restructure requirements and hardware section (#321)

Refactor the README to improve clarity by replacing the "Usage" section with a dedicated "Requirements" section. This includes:
- Adding specific hardware requirements (Microphone, CPU, Memory, Storage, OS).
- Updating recommended hardware configurations for better readability.
- Clarifying compatibility notes regarding Raspberry Pi Zero 2W and Respeaker Lite.

README.md

@@ -24,29 +24,34 @@ Because it runs on a full Linux system and offers access significantly more loca
 - Prebuild docker image available on [GitHub Container Registry](https://github.com/OHF-Voice/linux-voice-assistant/pkgs/container/linux-voice-assistant)
 - Prebuild [Raspberry Pi image](https://github.com/florian-asche/PiCompose)
 
-## Usage
+## Requirements
 
-### Hardware
+- Microphone: Device must support 16kHz mono audio
+- CPU: 1Ghz
+- Memory: min. 512MB
+- Storage: The OS and software is around 4GB
+- OS: linux/amd64 or linux/aarch64
 
 A more extensive list for possible compatible hardware can be found in the [PiCompose documentation](https://github.com/florian-asche/PiCompose) but basically any microphone that works with [PipeWire (multimedia framework for Linux)](https://pipewire.org/) can in theory be used for voice input with the prebuild image from there, you should however preferably use a far-field microphone-array solution if want better result. However if you're using your own USB microphone, **the microphone device must support 16kHz mono audio** for optimal voice recognition performance.
 
-Two solutions recommended for test setups today is to use a Raspberry Pi Zero 2 W SBC (Single Board Computer with built-in WiFi) in combination with the [Satellite1 Hat Board](https://futureproofhomes.net/products/satellite1-top-microphone-board) or the [Respeaker Lite](https://wiki.seeedstudio.com/reSpeaker_usb_v3/). Those have microphone-array designed for far-field voice capture with the added benefit of using an onboard XMOS DSP microcontroller with custom firmware which does advanced audio pre-processing for microphone cleanup that result in very good voice recognition capabilities (as it runs algorithms for Noise Suppression, Acoustic Echo Cancellation, Interference Cancellation, and Automatic Gain Control). 
+Two solutions recommended for setups today is:
 
-Alternatively if on a lower budget then suggest could try other untested microphone-array boards like example the [reSpeaker 2-Mics Pi HAT V2.0](https://wiki.seeedstudio.com/ReSpeaker_2_Mics_Pi_HAT/) (which uses a much more basic audio codec chip).
+- use a Raspberry Pi Zero 2W (Single Board Computer with built-in WiFi) in combination with the [Satellite1 Hat Board](https://futureproofhomes.net/products/satellite1-top-microphone-board)
+- use at least a Raspberry Pi 3 with the [Respeaker Lite](https://wiki.seeedstudio.com/reSpeaker_usb_v3/). The Respeaker Lite currently has a problem with the Zero 2W.
 
-As for the minimum required compute performance on these satellites the target reference hardware for testing is currently a 64-bit ARM-based SBC based on Raspberry Pi RP3A0 SiP (System-in-Package); which means the Raspberry Pi Zero 2 W, Raspberry Pi Compute Module 3E (Raspberry Pi CM3E), or other development boards that uses the Compute Module Zero" (Raspberry Pi CM0), as all of which have similar specifications to the Raspberry Pi 3 B/B+ but with a CPU running at a lower frequency.
+Those mic-boards have microphone-array designed for far-field voice capture with the added benefit of using an onboard XMOS DSP microcontroller with custom firmware which does advanced audio pre-processing for microphone cleanup that result in very good voice recognition capabilities (as it runs algorithms for Noise Suppression, Acoustic Echo Cancellation, Interference Cancellation, and Automatic Gain Control).
 
-But you can also install LVA on AMD64 devices, for example on your Linux desktop computer.
+Alternatively if on a lower budget then suggest could use other microphone-array boards like for example the [reSpeaker 2-Mics Pi HAT V2.0](https://wiki.seeedstudio.com/ReSpeaker_2_Mics_Pi_HAT/) (which uses a much more basic audio codec chip).
 
-### Software
+## Usage
 
-#### Installation
+### Installation
 
 For Raspberry Pi users, we provide a prebuild image that can be flashed to a SD card. See [PiCompose](https://github.com/florian-asche/PiCompose).
 
 For all other users, we have different installation methods available (Docker, systemd), each with its own dedicated instructions. See [Linux-Voice-Assistant - Installation](docs/install.md).
 
-#### Parameter overview
+### Parameter overview
 
 💡 **Note:** There is an [environment variable](docs/install_application.md#environment-variables-reference) for each parameter if you use docker or systemd based setup.
 
@@ -56,8 +61,9 @@ usage: __main__.py [-h] [--name NAME] [--audio-input-device AUDIO_INPUT_DEVICE]
                    [--mute-sound MUTE_SOUND] [--unmute-sound UNMUTE_SOUND] [--preferences-file PREFERENCES_FILE] [--host HOST] [--network-interface NETWORK_INTERFACE] [--port PORT] [--enable-thinking-sound] [--debug]
 ```
 
+
 | Parameter                  | Description                                                   | Default                           |
-|-----------|-------------|---------|
+| ---------------------------- | --------------------------------------------------------------- | ----------------------------------- |
 | `--name`                   | Name of the voice assistant device (required)                 | Autogenerated (`lva-MAC-ADDRESS`) |
 | `--audio-input-device`     | Soundcard name for input device                               | Autodetected                      |
 | `--audio-input-block-size` | Audio input block size in samples                             | 1024                              |
@@ -86,7 +92,6 @@ usage: __main__.py [-h] [--name NAME] [--audio-input-device AUDIO_INPUT_DEVICE]
 
 💡 **Note:** There is a detailed explanation on the gain, noise suppression, and wake word sensitivity flags in the [audio options](docs/audio_options.md) file.
 
-
 ## Build Information
 
 Image builds can be tracked in this repository's `Actions` tab, and utilize [artifact attestation](https://docs.github.com/en/actions/security-guides/using-artifact-attestations-to-establish-provenance-for-builds) to certify provenance.
@@ -104,6 +109,7 @@ The documentation for the build process can be found in the [GitHub Actions Work
 ### Code Quality Checks
 
 The project uses the following tools to ensure code quality:
+
 - **Black**: Code formatting (88 characters per line, PEP 8 compliant)
 - **isort**: Import sorting compatible with Black
 - **flake8**: Style and syntax checks
@@ -122,14 +128,16 @@ source .venv/bin/activate
 ### Linting Commands
 
 #### Run all linting checks
+
 ```sh
 ./script/lint...
 ```
 
 #### Individual linting commands (with auto-fix support)
 
+
 | Script                 | Description                              | Auto-fix Available?   |
-|--------|-------------|---------------------|
+| ------------------------ | ------------------------------------------ | ----------------------- |
 | `./script/lint_black`  | Checks Python code formatting with Black | Yes, use`--auto` flag |
 | `./script/lint_flake8` | Runs style and syntax checks with flake8 | No                    |
 | `./script/lint_isort`  | Checks import sorting with isort         | Yes, use`--auto` flag |
@@ -139,11 +147,13 @@ source .venv/bin/activate
 #### Examples
 
 Run a specific lint check:
+
 ```sh
 ./script/lint_black
 ```
 
 Auto-fix formatting issues (Black + isort):
+
 ```sh
 ./script/lint_black --auto
 ./script/lint_isort --auto
@@ -152,6 +162,7 @@ Auto-fix formatting issues (Black + isort):
 ### Testing
 
 Run the test suite:
+
 ```sh
 ./script/test
 ```