---
license: other
task_categories:
- other
- text-to-speech
- text-to-audio
language:
- en
tags:
- co-speech-gesture
- motion-generation
- speech
- smplx
- multimodal
size_categories:
- 10K<n<100K
---

# MotionSpeech: A Co-speech Gesture and Speech Dataset

**MotionSpeech** is a aligned multimodal dataset of **35,227 paired clips (~12.9 s each)** of
synchronized **speech audio** and **full-body SMPL-X motion**, with multi-layer
textual annotations. It is assembled from two public sources and re-segmented,
re-annotated and quality-filtered for training text-driven joint motion+speech
generative models.

| Source | Clips | Notes |
|---|---|---|
| [BEAT2](https://pantomatrix.github.io/BEAT2/) (English) | 18,063 | scripted monologue gestures, 30 speakers |
| [Seamless Interaction](https://github.com/facebookresearch/seamless_interaction) (improvised segments) | 17,164 | improvised English dyadic interaction |


## Directory structure

```
motionspeech_data_opensource/
├── README.md            this file
├── split/               official splits (sample IDs, one per line)
│   ├── train.txt        28,175
│   ├── val.txt           3,526
│   ├── test.txt          3,526
│   └── all.txt          35,227 (= train ∪ val ∪ test)
├── audio_wav/           <sample_id>.wav  mono 16-bit PCM
├── motion_smplx/        <sample_id>.npz  SMPL-X + FLAME pose sequence
└── caption/             <sample_id>.txt  multi-layer annotation (see below)
```

Every sample ID present in `split/` has all three data files (audio, motion,
caption) — the four modalities are strictly aligned.


## Sample ID convention

Two naming patterns, inherited from the sources:

- **BEAT2**: `{speaker_id}_{name}_{take}_{session}_{seg}_{start_frame}_{end_frame}`
  e.g. `10_kieks_0_10_10_1256_1642`
- **Seamless**: `V{video}_S{session}_I{interaction}_P{participant}_{start_frame}_{end_frame}`
  e.g. `V03_S1399_I00000495_P4044_7194_7580`

All files of one clip share the same ID (only the extension differs).


## Audio (`audio_wav/`)

- WAV, mono, 16-bit PCM.
- **BEAT2 clips are 16 kHz; Seamless clips are 48 kHz** (native rates of the
  sources are preserved — resample on load if a uniform rate is needed).
- Each clip is ~12.9 s, aligned 1:1 in time with its motion file.


## Motion (`motion_smplx/`)

Each `.npz` contains one clip at **30 fps** (387 frames ≈ 12.9 s):

| Key | Shape | Description |
|---|---|---|
| `poses` | (T, 165) | SMPL-X joint rotations in **axis-angle** (55 joints × 3) |
| `trans` | (T, 3) | global root translation (meters) |
| `expressions` | (T, 100) | FLAME facial-expression coefficients |
| `betas` | (300,) | SMPL-X body-shape coefficients |
| `model` | str | model identifier (`smplx+flame`) |
| `gender` | str | `male` / `female` |
| `mocap_frame_rate` | int | capture frame rate (30) |

Load with `numpy.load(path)`; drive SMPL-X+FLAME with the `poses/trans/betas`
to obtain meshes. (For 6D-rotation training features used in our baselines,
`poses` can be converted 3-axis-angle → 6D per joint.)


## Captions (`caption/`)

Each `.txt` holds four tagged layers concatenated in one line:

```
<L1>{one-sentence summary of the gesture}</L1>
<L2>{step-by-step detailed gesture description}</L2>
<S>{verbatim speech transcript, lowercase, no punctuation}</S>
<AUDCAP>{speaker voice description: gender, timbre, tone, pace}</AUDCAP>
```

Example (truncated):

```
<L1>The hands stay near the abdomen while the body shifts laterally, then both
palms open slightly outward.</L1>
<L2>First, both elbows remain bent and the hands are held apart in front of the
abdomen with gently curved fingers. Next, the hands move closer together ...
Finally, the hands remain low and open ...</L2>
<S>i would prefer to choose a major that is easy to find a good job in the
future like finance or marketing ...</S>
<AUDCAP>Female voice, clear and steady, speaking in an informative tone.</AUDCAP>
```

- `L1` / `L2` describe **co-speech body gestures** at two granularities.
- `S` is the **speech transcript** of the paired audio (already normalized to
  lowercase ASCII without punctuation).
- `AUDCAP` is a compact **speaker-voice caption** (gender / timbre / tone /
  pace) usable as a conditioning prompt for voice characteristics.


## Intended use

Text-driven / phoneme-driven joint generation of co-speech gesture and speech
(TTS-style audio + gesture avatars), gesture-speech synchronization research,
and captioning of multimodal speech+motion streams.


## License & attribution

This dataset is a re-segmentation and re-annotation of two public corpora.
Users must comply with the original licenses of
[BEAT2](https://pantomatrix.github.io/BEAT2/) and
[Seamless Interaction](https://github.com/facebookresearch/seamless_interaction),
and cite both sources in any derived work.