# Audio Tokenization Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/audio-tokenization
> Markdown URL: https://aitinkerers.org/technologies/audio-tokenization.md
> Technology record last updated: 2026-02-27T22:30:24Z
> Generated: 2026-10-22T20:56:36Z

Audio Tokenization converts continuous audio signals into discrete, machine-readable units (tokens), enabling efficient processing for AI models.

This technology transforms high-dimensional audio waveforms into compact sequences of discrete symbols: audio tokens. The core mechanism involves encoder-decoder architectures and quantization techniques, specifically Vector Quantization (VQ) or Residual Vector Quantization (RVQ), to map continuous features into a fixed codebook (e.g., 1024 vectors). These tokens, often representing short acoustic frames (e.g., 10-20 milliseconds), bridge the gap between raw sound and discrete computational processes. The result is highly efficient data compression and a format directly compatible with large language models (LLMs), which drives advanced applications like speech recognition, audio synthesis, and cross-modal alignment.

- Official technology site: https://poonehmousavi.github.io/dates-website/
- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Multi task audio models using auto regressive transformers](https://bengaluru.aitinkerers.org/talks/rsvp_2eKJ-4Lkk5E)

- Event context: AI Tinkerers Bangalore - November - RSVP REQUIRED — 2024-11-12 — Bengaluru
- Public talk page: https://bengaluru.aitinkerers.org/talks/rsvp_2eKJ-4Lkk5E

## Related Technologies

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- [Transformer](https://aitinkerers.org/technologies/transformer) ([Markdown](https://aitinkerers.org/technologies/transformer.md)) — 11 public demos