Audio is roughly a third of our media time but only a small percentage of ad spend. Insights from Bayer, Ovative, and SiriusXM on why marketers are planning audio earlier, and measuring it beyond clicks.

Audio8 ASR Infinite streaming speech recognition model the native streaming architecture decodes 12.5 times per second a rolling KV Cache keeps both memory and latency constant, even in 24/7 operation one text token per clock step (12.5 / 8.3 / 6.25 decisions per second), balancing perception granularity and resource cost ML intern in huggingchat setup a gradio workflow to try it out: huggingchat: model:

Audio8 ASR Infinite keeps transcribing around the clock with bounded memory and latency. 🤖 🎙️ A rolling KV Cache enables unlimited-length Chinese and English transcription without accumulated drift. 🏆 At 480 ms delay, it reaches 1.75 CER on AISHELL-1, 2.89 on AISHELL-4, and 3.04/6.81 WER on LibriSpeech test-clean/test-other. ⚡ Select an 80, 120, or 160 ms audio clock and tune delay from 240 to 560 ms. Semantic VAD distinguishes pauses from real turn endings. 📜 Preview release under Apache 2.0, with continuous deployment through an adapted vLLM stack.

Audio8 TTS Preview 0.1B — now on Hugging Face as ONNX INT8 ~100M params · 11 languages · zero-shot voice cloning Runs on CPU only (~0.4 GB RAM) — no PyTorch, no CUDA 44.1 kHz · OpenAI-compatible API · Apache 2.0 Try it 👇 #TTS# #VoiceCloning# #ONNX# #OpenSource#