glemöhnic

Övrigt konferensbidrag, 2024

glemöhnic is a ~20 minute performance piece that utilises SpeechBrain, OpenAI and CoquiTTS voice and speech models to transcribe, synthesise and clone historical and real-time improvised vocal gestures.

This piece explores how extra-normal [undefined] vocal sounds trigger and provoke nonsensical AI-mediations of human vocality, by utilising non-text audio as input material for text-expectant AI speech recognition and synthesis models. The mediation of non-textual human voice gestures by these ASR models yields eclectic, bizarre and poetic nonsense, which is further utilised as textual input for text-to-speech synthesis and voice cloning models. CoquiTTS’ XTTS_V2 model re-constructs the syllabic, phonemic and garbled poems into vocal clones that oscillate between their reference audio (the original audio dataset input) and the scraped audio data that the XTTS_V2 model has been trained on. The result of this is a collection of original and cloned audio samples that are utilised as sonic material in a live coded musical performance, using the strudelREPL platform.