Datasets:
Languages:
English
Size:
n<1K
ArXiv:
Tags:
motion-generation
co-speech-gesture-generation
streaming-generation
beat2
smpl-x
arxiv:2608.01643
License:
| license: other | |
| pretty_name: StreamTalk Inference Data | |
| language: | |
| - en | |
| tags: | |
| - motion-generation | |
| - co-speech-gesture-generation | |
| - streaming-generation | |
| - beat2 | |
| - smpl-x | |
| - arxiv:2608.01643 | |
| size_categories: | |
| - n<1K | |
| # StreamTalk Inference Data | |
| Ready-to-compare SMPL-X predictions from the official retrained StreamTalk CFG checkpoints. This release follows the convenient inference-data style of [SemTalk](https://github.com/Xiangyue-Zhang/SemTalk): users can download generated test outputs and evaluate or visualize them without rerunning WavLM, retrieval, diffusion sampling, and SMPL-X conversion. | |
| - [Paper](https://arxiv.org/abs/2608.01643) · [Hugging Face Paper page](https://huggingface.co/papers/2608.01643) | |
| - [Project page](https://xiangyuezhang.com/StreamTalk/) · [Code](https://github.com/Xiangyue-Zhang/StreamTalk) | |
| - [Model checkpoints](https://huggingface.co/X-Zhang/StreamTalk) | |
| No BEAT2 ground-truth motion, audio, training cache, or model checkpoint is included in these archives. | |
| ## Downloads | |
| | Scope | Clips | Checkpoint | CFG | Archive | SHA-256 | | |
| | :-- | --: | :-- | --: | :-- | :-- | | |
| | Speaker 2 (Scott) | 15 | epoch 946 | 3 | [download](https://huggingface.co/datasets/X-Zhang/StreamTalk-Inference-Data/resolve/main/streamtalk_speaker2_e0946_cfg3_npz.tar.gz) | `859cb968c04804a797e3f8eb17aeba1f91bda29305f970564c9be481e41fa452` | | |
| | All speakers | 265 | epoch 940 | 3 | [download](https://huggingface.co/datasets/X-Zhang/StreamTalk-Inference-Data/resolve/main/streamtalk_all_e0940_cfg3_npz.tar.gz) | `295d933883dc40acb9df5f2d2ba02767ec62c9d83f423a78900932499fc8edb4` | | |
| ```bash | |
| wget https://huggingface.co/datasets/X-Zhang/StreamTalk-Inference-Data/resolve/main/streamtalk_speaker2_e0946_cfg3_npz.tar.gz | |
| wget https://huggingface.co/datasets/X-Zhang/StreamTalk-Inference-Data/resolve/main/streamtalk_all_e0940_cfg3_npz.tar.gz | |
| sha256sum -c SHA256SUMS | |
| tar -xzf streamtalk_speaker2_e0946_cfg3_npz.tar.gz | |
| tar -xzf streamtalk_all_e0940_cfg3_npz.tar.gz | |
| ``` | |
| ## Released FGD re-score | |
| The downloadable NPZ bytes were independently re-scored with the StreamTalk release scorer and the pinned EMAGE/PantoMatrix AESK encoder (`SHA-256 5cd9566b...c40f55`). Equal-length metric batching uses batch size 16. | |
| | Scope | Archive re-score FGD ↓ | Selection-time FGD ↓ | Absolute difference | | |
| | :-- | --: | --: | --: | | |
| | Speaker 2 (Scott) | **0.3788789702354345** | 0.3788789702354416 | 7.1e-15 | | |
| | All speakers | **0.21764184426140076** | 0.21767150775461275 | 2.97e-5 | | |
| Both differences are below the selected engineering reporting tolerance of `1e-3`. These are accelerated EMAGE/AESK measurements, not a claim of paper-exact B=1/M=1/full-window bitwise equivalence. See `speaker2_fgd.json` and `all_fgd.json` for the complete metric contract. | |
| ## NPZ schema | |
| Every archive contains one `res_<BEAT2-test-id>.npz` per official test ID plus a scope manifest. Load files with `allow_pickle=False`. | |
| | Key | Shape/type | Meaning | | |
| | :-- | :-- | :-- | | |
| | `poses` | `[T, 165]`, float32 | local SMPL-X axis-angle rotations | | |
| | `trans` | `[T, 3]`, float32 | root translation | | |
| | `expressions` | `[T, 100]`, float32 | facial expression coefficients | | |
| | `betas` | `[300]`, float32 | body-shape coefficients | | |
| | `gender` | string | body-model metadata | | |
| | `mocap_frame_rate` | scalar | 30 FPS | | |
| | `model` | string | `smplx2020` | | |
| ```python | |
| import numpy as np | |
| with np.load("res_2_scott_0_1_1.npz", allow_pickle=False) as motion: | |
| poses = motion["poses"] | |
| expressions = motion["expressions"] | |
| trans = motion["trans"] | |
| ``` | |
| ## Re-score with StreamTalk | |
| The generated files do not include BEAT2 ground truth. After obtaining BEAT2 under its own terms, use the scorer in the [StreamTalk repository](https://github.com/Xiangyue-Zhang/StreamTalk): | |
| ```bash | |
| python tools/evaluate_generated_fgd.py \ | |
| --predictions streamtalk_speaker2_e0946_cfg3_npz \ | |
| --ground_truth /path/to/beat_english_v2.0.0/smplxflame_30 \ | |
| --scope speaker2 --device cuda:0 --metric_batch_size 16 | |
| python tools/evaluate_generated_fgd.py \ | |
| --predictions streamtalk_all_e0940_cfg3_npz \ | |
| --ground_truth /path/to/beat_english_v2.0.0/smplxflame_30 \ | |
| --scope all --device cuda:0 --metric_batch_size 16 | |
| ``` | |
| ## Provenance and terms | |
| - Generator code: StreamTalk training/evaluation commit `b6cac99d5bae5164a21f5db25afef72c3c30556a`. | |
| - Speaker 2 checkpoint SHA-256: `07065d52e333cc48960e4e8fad5c0331f6b9e482f14aa1b78cb721904da5b075`. | |
| - All-speaker checkpoint SHA-256: `3a0e3558d788fd3f11a5a87a8198b42725104b5b9b24f95a4e7c84c14395c9a5`. | |
| - Seed: 0. Speaker 2 generation uses clip batch 1; all-speaker generation uses clip batch 16; both use CFG 3 and an 8-frame retrieval query. | |
| The predictions are derived from experiments on BEAT2 and use the SMPL-X body model. Users remain responsible for complying with the licenses and terms of the [BEAT2 dataset](https://huggingface.co/datasets/H-Liu1997/BEAT2) and [SMPL-X](https://smpl-x.is.tue.mpg.de/). This dataset card does not redistribute BEAT2 ground truth, audio, or SMPL-X model files. | |