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EmbodiedBench-Audio

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Add clean_embodied/: 300 EmbodiedBench-Audio samples (TTS + images + CSV)

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+ ---
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+ license: mit
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+ language:
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+ - en
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+ pretty_name: EmbodiedBench-Audio (clean speech, 300 samples)
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+ size_categories:
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+ - n<1K
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+ tags:
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+ - embodiedbench
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+ - alfred
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+ - speech
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+ - multimodal
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+ - omniagentbench
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+ ---
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+
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+ # EmbodiedBench-Audio · `clean_embodied/`
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+
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+ 300-sample speech extension of [EmbodiedBench](https://arxiv.org/abs/2502.09560) / [EB-ALFRED](https://huggingface.co/datasets/EmbodiedBench/EB-ALFRED). Each row pairs a household task with **clean TTS audio**, the **starting-frame image**, and the original natural-language goal + ground-truth high-level plan.
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+
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+ This folder is the **clean** variant. Other contributors can add `noisy_embodied/`, `wild_embodied/`, etc. alongside.
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+
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+ ## Layout
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+
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+ ```
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+ clean_embodied/
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+ ├── README.md (this file)
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+ ├── Embodied_task.csv (300 rows · 7 columns — the source of truth)
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+ ├── audio/
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+ │ ├── manifest.json (sample_id → audio file + all CSV fields)
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+ │ └── embodied_<trial>_<repeat_idx>.wav (300 files · 24 kHz mono · ~35 MB)
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+ └── images/
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+ └── <trial>_<repeat_idx>.png (300 files · ~33 MB)
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+ ```
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+
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+ ## CSV columns (Embodied_task.csv)
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+
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+ | Column | Description |
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+ |---|---|
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+ | `trial` | ALFRED trial id, e.g. `trial_T20190908_044113_026049` |
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+ | `repeat_idx` | Annotator index (0–N), each trial has multiple paraphrasings of the same goal |
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+ | `scene` | AI2-THOR scene id, e.g. `FloorPlan219` |
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+ | `goal_instr` | One-sentence high-level goal — the **input text** the agent receives |
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+ | `gt_high_descs` | List of step-by-step natural-language descriptions — auxiliary annotation |
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+ | `gt_high_pddl_actions` | List of symbolic ground-truth actions (`GotoLocation`, `PickupObject`, …) — gold answer |
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+ | `image_name` | Filename of the starting frame in `images/` |
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+
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+ ## Pairing audio ↔ image ↔ CSV row
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+
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+ ```python
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+ # sample_id is shared by audio (with prefix) and image (without prefix)
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+ sample_id = f"embodied_{trial}_{repeat_idx}"
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+ audio_path = f"clean_embodied/audio/{sample_id}.wav"
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+ image_path = f"clean_embodied/images/{trial}_{repeat_idx}.png"
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+ ```
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+
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+ ## Audio characteristics
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+
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+ - **TTS model:** [`Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign`](https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign)
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+ - **Voice instruct:** *"Speak naturally and clearly as if giving a household task instruction to a robot assistant"*
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+ - **Format:** 24 kHz mono WAV
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+ - **Duration:** 1.2–5.1 s per WAV (median 2.3 s) — bounded by source text length (median 9 words)
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+ - **Speech rate:** ~208 wpm
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+ - **Generated:** 2026-05-03 on a single NVIDIA RTX PRO 6000 Blackwell, ~10 min wall time for 300 samples
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+
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+ ## Source data
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+
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+ The text, image, and ground-truth fields are derived from the [EB-ALFRED](https://huggingface.co/datasets/EmbodiedBench/EB-ALFRED) subset of [EmbodiedBench](https://arxiv.org/abs/2502.09560), which itself is built on [ALFRED](https://github.com/askforalfred/alfred) (Shridhar et al., CVPR 2020).
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+
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+ - **EmbodiedBench:** Yang et al., 2025 ([arXiv:2502.09560](https://arxiv.org/abs/2502.09560))
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+ - **ALFRED:** Shridhar et al., CVPR 2020 ([alfred.github.io](https://askforalfred.com/))
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+
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+ If you use this audio extension, please also cite the upstream works.
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+
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+ ## Citation
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+
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+ ```bibtex
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+ @misc{omniagentbench_embodied_audio_2026,
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+ title = {EmbodiedBench-Audio: clean speech for the EmbodiedBench 300-sample subset},
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+ author = {OmniAgentBench Team},
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+ year = {2026},
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+ url = {https://huggingface.co/datasets/omniagentbench/EmbodiedBench-Audio}
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+ }
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+ ```
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+
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+ Part of the [OmniAgentBench](https://huggingface.co/datasets/omniagentbench/OmniAgentBench) project.
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