GoKawiilOpen-source project Tiny Audio trains speech-to-text models for about $25
Tiny Audio is a GitHub project that pairs a frozen pretrained speech encoder with a pretrained LLM through a small trainable projector, requiring only about 80 million trainable parameters. The released model reaches 1.8% word error rate on LibriSpeech test-clean and 7.4% across a pooled set of 12 benchmarks, and the codebase can reportedly be read in an afternoon or trained on a laptop in roughly five minutes. It also supports word-level timestamps and speaker diarization via a zero-shot port of NVIDIA's NeMo masked_asr recipe.