Audio Tokenization

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.

https://poonehmousavi.github.io/dates-website/