Get the whole recording (total length: 0:47:33) on Bandcamp now:
https://randyedgewood.bandcamp.com/track/expedition-16-ultratech-chaos-lab-10-local

Here is the recording of an ephemeral liveset I created for Ultratech Chaos Lab 1.0, the first instalment of a party series dedicated to experimental music and digital art. The event took place at le Local Bar, a great venue located in Strasbourg, and well known for its crafted beers and rock concerts. Even if there were few people, the vibe was great, and I remember very well this special feeling of complete freedom I had during my performance. Hence the last part that wasn't supposed to be that long initially.

Special thanks to the Local Bar team for hosting this event, and big up to all the other artists involved: Comtesse du Ghetto, Coloscope, and Crash Server.

Live setup: Reason + MIDI controllers
Recording: Zoom H5

Photo credit: Alice Dirwimmer

Expedition 16: Ultratech Chaos Lab 1​.​0 (Local) [Intro]

||| Emergence |||
Dark ambient meets downtempo in this haunting track. 

+ Listen on Spotify +
https://open.spotify.com/album/70bXj7TuYqK4cggyUWc2fQ

Watch the video here 
https://www.youtube.com/watch?v=67DzyxoF7UU

Walking The Black Dog

Emergence

Download

Original Track By::
https://soundcloud.com/asdb_music/time-prime
Photo By Ivons

as.dB - Timeprime (Senglar Rmx)

SenSen - Heroína

SenSen - Blind & Dumb & Deaf

# Audio Processing Rules

## Overview
This code processes 30 sound files from a specified folder and combines them into a single WAV file according to the following algorithmic composition rules.

## Processing Rules

### 1. Source Material
- **Input**: Up to 30 audio files from a designated folder
- **Supported formats**: WAV, MP3, M4A, FLAC, AAC, OGG
- Files are randomly selected if more than 30 are present in the folder

### 2. Fragment Extraction
- **Fragments per file**: 3-5 segments are extracted from each audio file
- **Fragment duration**: Random length, with a maximum of 5 seconds per fragment
- **Selection method**: Random start points are chosen within each source file
- **Minimum fragment length**: 0.5 seconds

### 3. Randomization Process
- **Shuffling**: All extracted fragments are randomly reordered
- **No preservation**: Original file sequence and internal fragment order are completely randomized

### 4. Silence Insertion
- **Probability**: 1/7 chance (approximately 14.3%) after each fragment
- **Duration**: Random silence between 0.5-2.0 seconds
- **Placement**: Silence is inserted between fragments, not at the beginning or end

### 5. Output Generation
- **Format**: Single WAV file
- **Combination method**: Linear concatenation of randomized fragments with occasional silence
- **Quality**: Maintains original audio quality of source materials

## Algorithmic Composition Characteristics

This process creates an **aleatoric** (chance-based) musical composition where:
- The final arrangement is determined by random algorithms rather than compositional intent
- Each execution produces a unique result due to randomization
- The work explores the relationship between **sound, silence, and time**
- Multiple source materials are democratically combined without hierarchical preference

## Technical Implementation
- Built using Python with `pydub` library for audio processing
- Designed for Jupyter Notebook environment
- Includes error handling for various audio file formats and edge cases

Fragments of Memory

Places we have been - they guide us somehow. Sometimes even if we only have been dreaming of beeing there.

In the streets of Osaka there is a lot of melodic sounds in the air. From traffic lights, garbage collections, mobile traders selling ramen soup... 

In this track everything you hear is from field recordings made by @maguri - thank you Martin!

Osaka

MMXVIIIVIIIXXIIIRTFTHTS

Each generation must, out of relative obscurity, discover its mission, fulfill it, or betray it

Puerto Sur

Ivons & Senglar - Lobomental

Latest Albums :
https://senglarbraille.bandcamp.com/album/jt-chapman-senglar-susurrus
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https://elmuellerecords.bandcamp.com/album/hum
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https://martinhoogeboom.bandcamp.com/track/fearless-senglar-version-a