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Interactive sound


* inputs in microcontrollers for preprocessing interface to PC for further processing.
* it’s also possible to have microcontroller standalone applications

website

soundhacking.github.io

github organisation

github.com/SoundHacking

Debug workflow

* it’s possible to debug an embedded sound processing system by injecting packets and retrieving the results

Topics

Offline Preparation

The Offline preparation is a necessary step to understand the signal and condition it for the target application where it will be used, that’s where Python with its scientific toolkits and machine learning environment will be used.

* Signal Analysis
* Machine Learning

Real Time Processing

Smart applications are ones that instantly react to the user in an interactive, collaborative or assistive mode such as during tracking. Therefore an instant response of the system is what creates a feeling of connection with the instrument.

Real time Audio processing requires dedicated hardware acceleration to prevent delays.

Capture

It’s about capture of audio and other user inputs. Audio goes through I2S microphone arrays connected to microcontrollers. Other user inputs can be accelerometer or touch interfaces that are to be used as control for sound generation

* Microphones
* Accelerometers
* smart touch surface
* USB interfaces (Audio / HID / Serial Data)

Display

The output should not only be hearable as a sound signal but also visual in order to assist the interaction.

webapp view of live audio signal
Status feedback through LEDs

Microcontrollers

* STM32 based on ARM-M4 with USB connections and other I2S peripherals
* Black pill : STM32F411 (USB)
* Audio Discovery : STM32F407 (USB, stereo out)
* DevEBox : STM32F407 (USB, SDCARD)
* ESP32 (wifi / BT)
* nRF52 (custom RF / BT)
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