Eric Bezzam

One of the biggest changes in the history of 🤗 Transformers audio is in the works, spearheaded by @eustachelb We’re rebuilding essentially the entire audio preprocessing stack. The goal is to move away from every model carrying its own `FeatureExtractor` implementation, and towards a common `AudioProcessor` architecture where models describe their frontend, while shared backends handle the actual computation. The stack currently covers ~30 audio frontends and 62 model mappings across Whisper, Wav2Vec2, Parakeet, SeamlessM4T, Qwen, Gemma, codecs, TTS models,and many others. A big part of the work is making backends explicit: `backend="torch"` → native PyTorch preprocessing (often super fast!) `backend="numpy"` → portable NumPy preprocessing That means audio preprocessing can increasingly live in the same framework as the model itself, while still keeping compatibility with the numerical behavior existing checkpoints expect. It also gives us a much better foundation for what comes next: new hardware backends, faster kernels, compilation, and optimizations that can benefit many audio models at once instead of being implemented model by model. ~30 frontends migrated. 62 model mappings. One common preprocessing architecture. The entrypoint, common across all architectures: `AutoAudioProcessor.from_pretrained(...)` Audio in Transformers is about to get a much stronger foundation! 🎧🎧🎧