Echo Archive: Crowd-Sourced Audio Library for AI & Human Voice Analysis


Storytelling, Digital Product Design


Lisa Plesiutschnig, Grzegorz Jaszczyk



Echo Archive is the first independent voice archive where voices are organized based on distinct characteristics. This project captures the uniqueness of individual voice samples and explores the subjective perceptions, inviting users to engage with and reflect on the nuances of spoken language and its impact.

The primary aim of Echo Archive is to create an intuitive and comprehensive classification system for voice snippets. It is an evolving experiment that grows with each new voice sample added. The goal is to catalog these snippets into 100 distinct categories based on their auditory characteristics and to make these classifications accessible and perceptible through an online audio library.

The process involves meticulous recording of voice samples within the team’s personal networks, followed by a detailed classification based on a pre-defined scheme. This scheme is crafted and tested to capture a wide array of voice qualities and attributes, making the archive a rich resource for understanding voice diversity.

Echo Archive stands as a testament to the power of voice and sound in shaping human connections and experiences. By systematically classifying and sharing voice samples, the project not only enriches our understanding of auditory elements but also challenges early AI voice classification.

Currently based in Berlin / Zürich