--- title: SpotSound Temporal Grounding emoji: 🔍 colorFrom: indigo colorTo: pink sdk: gradio sdk_version: 6.24.0 app_file: app.py short_description: Find when a described sound happens in a recording python_version: '3.12' startup_duration_timeout: 1h --- # SpotSound — fine-grained audio temporal grounding Demo of **[SpotSound](https://huggingface.co/Loie/SpotSound)** (Sun et al., 2026), a LoRA on top of [NVIDIA Audio Flamingo 3](https://huggingface.co/nvidia/audio-flamingo-3-hf) that gives large audio–language models fine-grained temporal grounding: given a long, untrimmed recording and a natural-language query, it answers with the start/end timestamps of the described sound event. * Paper: * Project page: * Code: * Benchmark: ## How it works `spotsound.py` ports the two pieces of the official implementation onto current `transformers`: 1. **Timestamp-interleaved audio tokens** — the `` placeholder is expanded to `"timestamp: t seconds; feature: " + × 25` for every second of audio (AF3 produces exactly 25 post-pool audio tokens per second), so the language model can read absolute time off the audio stream. 2. **Tolerant audio scatter** — the audio features are scattered into the audio-token slots without the base class's strict `#tokens == #features` check, since the interleaving keeps `floor(N / 25) × 25` of the `N` features. The published LoRA adapter is merged into the base model at startup and served on ZeroGPU. ## Examples The four example clips come from [Loie/SpotSound-Bench](https://huggingface.co/datasets/Loie/SpotSound-Bench) (MIT licensed), the paper's own "needle-in-a-haystack" benchmark. ## Licensing The SpotSound adapter and benchmark are MIT licensed. The base model, `nvidia/audio-flamingo-3-hf`, is released under the NVIDIA OneWay Noncommercial License — this demo is for research/non-commercial use.