README.md

---
license: other
license_name: see-license.md
license_link: LICENSE.md
task_categories:
  - feature-extraction
  - audio-classification
language:
  - multilingual
tags:
  - speech
  - prosody
  - acoustic-features
  - multilingual
  - phonetics
  - biometric-privacy
  - linguistics
pretty_name: Moonscape Human Speech Atlas (HSA)
size_categories:
  - 100K<n<1M
extra_gated: true
extra_gated_prompt: "To access the Moonscape Human Speech Atlas, please provide your institutional details and agree to the biometric privacy terms. NOTE: Requests utilizing non-institutional emails (@gmail, @hotmail, @yahoo, @outlook, etc.) will be automatically rejected for the Restricted Tier."
extra_gated_fields:
  Full Name: text
  Organization or Affiliation: text
  Country / Jurisdiction of Organization: text
  Intended Use Case (Brief description of your research or application): text
  Licensing Tier Requested:
    type: select
    options:
      - "Tier 1: Academic / Non-Commercial (Moonscape Tier 1 License)"
      - "Tier 2: Commercial Use — Single user or site (Requires external EULA)"
      - "Tier 3: Commercial Use — Multiple users or sites (Requires external EULA)"
  I agree to the Non-Commercial use restriction (if selecting Tier 1):
    type: checkbox
  I agree to NEVER attempt human speaker re-identification or unmasking:
    type: checkbox
  I agree to NEVER alter, truncate, or remove the forensic watermarks (seeded noise):
    type: checkbox
  I agree to comply with upstream Mozilla Common Voice CC0 terms:
    type: checkbox
configs:
  - config_name: Indo-European
    default: true
    data_files: data/Indo-European/*.parquet
  - config_name: Niger-Congo
    data_files: data/Niger-Congo/*.parquet
  - config_name: Austronesian
    data_files: data/Austronesian/*.parquet
  - config_name: Mesoamerican
    data_files: data/Mesoamerican/*.parquet
  - config_name: Americas-Other
    data_files: data/Americas-Other/*.parquet
  - config_name: Afro-Asiatic
    data_files: data/Afro-Asiatic/*.parquet
  - config_name: Nilo-Saharan
    data_files: data/Nilo-Saharan/*.parquet
  - config_name: Trans-New-Guinea
    data_files: data/Trans-New-Guinea/*.parquet
  - config_name: Eurasian-Minor
    data_files: data/Eurasian-Minor/*.parquet
  - config_name: Turkic
    data_files: data/Turkic/*.parquet
  - config_name: Asian-Minor
    data_files: data/Asian-Minor/*.parquet
  - config_name: Isolates
    data_files: data/Isolates/*.parquet
---

# Moonscape Human Speech Atlas (HSA)

**Moonscape Software — Human Speech Atlas**

A curated corpus of pre-extracted acoustic feature matrices for multilingual prosody
research. The HSA covers **90+ languages across 12 linguistic family trees**, derived
from Mozilla Common Voice (CV24.0) and Spontaneous Speech (SPS2.0) — both CC0.

The HSA is a companion project to the **Synthetic Speech Atlas (SSA)**, which provides
parallel feature-space representations of synthetic and bonafide speech for deepfake
detection. Together they form a complete acoustic telemetry platform.

Audio files are **not included**. Each file is a Snappy-compressed Parquet dataset of
38 hand-crafted classical signal-processing features extracted via Parselmouth/Praat
and Brouhaha, with full biometric protection applied at export.

> **Export version:** HSA_v1_2026
> **Anonymization standard:** `moonscape_k5_fp16_v1`
> **Watermark:** HMAC-SHA256 seeded FP16-resolution noise per column

---

## Repository Structure

This is a single gated repository. All 12 linguistic family trees are available as
**named subsets (configurations)** within it. Each subset maps to a subdirectory of
Parquet files under `data/`.

```
Human_Speech_Atlas/
├── README.md
├── LICENSE.md
└── data/
    ├── Indo-European/        ← ~148K cream clips, 50 tables
    ├── Niger-Congo/          ← ~144K cream clips, 34 tables
    ├── Austronesian/         ← ~46K cream clips, 17 tables
    ├── Mesoamerican/         ← ~28K cream clips, 13 tables
    ├── Americas-Other/       ← ~16K cream clips, 4 tables
    ├── Afro-Asiatic/         ← ~14K cream clips, 5 tables
    ├── Nilo-Saharan/         ← ~12K cream clips, 4 tables
    ├── Trans-New-Guinea/     ← ~11K cream clips, 3 tables
    ├── Eurasian-Minor/       ← ~8K cream clips, 8 tables
    ├── Turkic/               ← ~8K cream clips, 6 tables
    ├── Asian-Minor/          ← ~8K cream clips, 10 tables
    └── Isolates/             ← ~6K cream clips, 2 tables
```

### Loading a Subset

```python
from datasets import load_dataset

# Load a single family tree
df = load_dataset("moonscape-software/Human_Speech_Atlas", "Indo-European")

# Load multiple trees
indo = load_dataset("moonscape-software/Human_Speech_Atlas", "Indo-European")
niger = load_dataset("moonscape-software/Human_Speech_Atlas", "Niger-Congo")

# Load all trees (large — ~531K rows total)
all_trees = {
    tree: load_dataset("moonscape-software/Human_Speech_Atlas", tree)
    for tree in [
        "Indo-European", "Niger-Congo", "Austronesian", "Mesoamerican",
        "Americas-Other", "Afro-Asiatic", "Nilo-Saharan", "Trans-New-Guinea",
        "Eurasian-Minor", "Turkic", "Asian-Minor", "Isolates"
    ]
}
```

---

## Family Tree Index

| Subset (config_name) | Languages | Cream Clips | Notable Languages |
|----------------------|-----------|-------------|-------------------|
| `Indo-European` | 50 tables | ~148K | Hindi, Cornish, Gujari, Dhatki, Khowar, Kalasha, Manx, Lasi, Gawri |
| `Niger-Congo` | 34 tables | ~144K | Hausa, Nawdm, Massa, Chokwe, Fang, Igbo, Cameroon Grassfields |
| `Austronesian` | 17 tables | ~46K | Seediq, Batak Toba, Gotontalo, Cuyonon, Melanau |
| `Mesoamerican` | 13 tables | ~28K | Tzeltal, 3x Mazatec, Mixtec, Totonac, Huichol |
| `Americas-Other` | 4 tables | ~16K | Central Alaskan Yupik, Seri, Quechua |
| `Afro-Asiatic` | 5 tables | ~14K | Hausa, Hebrew, Tashlhiyt Berber |
| `Nilo-Saharan` | 4 tables | ~12K | Dinka Ruweng, Kenyan Luo |
| `Trans-New-Guinea` | 3 tables | ~11K | Mauwake, Ukuriguma (Papuan deep-time) |
| `Eurasian-Minor` | 8 tables | ~8K | Adyghe, Kabardian, Lak, Moksha, Votic |
| `Turkic` | 6 tables | ~8K | Kazakh, Tuvan, Bashkir |
| `Asian-Minor` | 10 tables | ~8K | Min Dong, Puxian Min, Keazi, Bodo |
| `Isolates` | 2 tables | ~6K | Korean, Georgian |

> Clip counts are post-k-anonymisation (k=5). Rows where quasi-identifier groups
> contain fewer than 5 members are suppressed.

---

## Why This Dataset Exists

Cross-linguistic prosody research is underserved by existing open corpora.
The HSA enables researchers to:

- Study prosodic typology across genetically unrelated language families
  in a single unified schema and a single gated repository
- Train cross-lingual speech models without audio infrastructure
- Benchmark acoustic features across tonal, stress-timed, and syllable-timed languages
- Use the **Isolates** subset (Korean, Georgian) as a control group for studying
  convergent vs inherited prosodic features
- Access rare and endangered language data — Votic (~5 remaining speakers),
  Tashlhiyt Berber (consonant-only syllabics), Trans-New Guinea Papuan languages

---

## Privacy & Legal Framework

### Why This Corpus Is Gated

These files contain acoustic features derived from recordings of real human speakers.
Although audio is not included, acoustic feature vectors carry residual biometric
information. The following controls are applied:

1. Access restricted to verifiable institutional actors
2. Non-institutional emails rejected at intake
3. Commercial use requires a separate EULA with Moonscape Software
4. All users agree to non-re-identification and watermark integrity obligations

### Biometric Protection Measures — `moonscape_k5_fp16_v1`

1. **UID link cut** — `file_id`, `client_id`, `source_file`, and `transcript`
   stripped entirely. No path back to source speaker or sentence identifiers.

2. **K-anonymity (k≥5)** — Rows suppressed where the quasi-identifier group
   `{gender, age_bucket, duration_bucket}` contains fewer than 5 members.

3. **Duration bucketing** — `duration_ms` rounded to nearest 100ms.

4. **Precision reduction** — All continuous acoustic variables rounded to 2dp.

5. **FP16 reinflation watermark** — Each 2dp-rounded value is reinflated with
   deterministic FP16-resolution seeded noise:

   ```
   seed  = HMAC-SHA256(HSA_EXPORT_SECRET, col_name + "|HSA_v1_2026")
   noise ~ Uniform(-0.004, +0.004)  [seeded deterministically per column]
   value = float16(round(raw, 2) + noise)  [stored as float32]
   ```

   This destroys the backward-engineering path to raw biometric values while
   preserving statistical validity. Every row carries a unique verifiable
   provenance signature.

### Source Data License

All source audio is Mozilla Common Voice CV24.0 (CC0-1.0) and Mozilla Spontaneous
Speech SPS2.0 (CC0-1.0). No audio is redistributed. Feature extraction pipeline
and methodology are copyright Moonscape Software.

---

## Dataset Schema

All HSA parquet files share an identical 46-column canonical schema regardless of
language, family tree, or source corpus. Column order is fixed.

### Identity & Provenance

| Column | Type | Description |
|--------|------|-------------|
| `clip_id` | string | Anonymous sequential ID. Format: `{lang_corpus_NNNNNN}` |
| `lang_code` | string | ISO 639-3 language code (e.g. `ko`, `ha`, `btv`) |
| `lang_name` | string | Human-readable language name |
| `corpus` | string | Source corpus: `cv24` or `sps2` |
| `speech_type` | string | `scripted` (CV24) or `spontaneous` (SPS2) |
| `source_dataset` | string | Full source name (e.g. `Mozilla Common Voice CV24.0`) |
| `sentence_domain` | string | Text domain: `wikipedia` \| `news` \| etc. |

### Demographics

| Column | Type | Description |
|--------|------|-------------|
| `gender` | string | `male` \| `female` \| `other` \| `unknown` |
| `age` | string | Age bracket (e.g. `20-29`) or `unknown` |
| `accent` | string | Self-reported accent/dialect label |
| `dialect_tag` | string | Normalised dialect code |
| `sample_type` | string | `cream_t1` \| `cream_t2` \| `fill_t3` \| `fill_t4` |

### Temporal

| Column | Type | Description |
|--------|------|-------------|
| `duration_ms` | Int64 | Clip duration bucketed to nearest 100ms |
| `duration_s` | float32 | `duration_ms / 1000` |

### Quality Gate (Brouhaha)

| Column | Type | Description |
|--------|------|-------------|
| `tier` | int | 1=PRISTINE 2=STUDIO 3=AMBIENT 4=TRASH |
| `tier_label` | string | `PRISTINE` \| `STUDIO` \| `AMBIENT` \| `TRASH` |
| `snr_median` | float32 | Median signal-to-noise ratio (dB) |
| `snr_mean` | float32 | Mean SNR (dB) |
| `c50_median` | float32 | Median room clarity C50 (dB) |
| `speech_ratio` | float32 | Active speech fraction (0-1) |

### Acoustic Features (float32, FP16 watermarked)

| Column | Units | Description |
|--------|-------|-------------|
| `pitch_mean` | Hz | Mean F0 (VAD-bounded, voiced frames only) |
| `pitch_std` | Hz | F0 standard deviation |
| `pitch_range` | Hz | 95th-5th percentile F0 |
| `pitch_velocity_max` | Hz/frame | Max F0 rate-of-change |
| `jitter_local` | % | Cycle-to-cycle period variation (MP3 fidelity caveat) |
| `shimmer_local` | % | Cycle-to-cycle amplitude variation (MP3 fidelity caveat) |
| `hnr_mean` | dB | Harmonics-to-noise ratio |
| `cpps` | — | Cepstral peak prominence smoothed |
| `intensity_mean` | dB | Mean intensity (normalised — see limitations) |
| `intensity_max` | dB | Peak intensity (normalised — see limitations) |
| `intensity_range` | dB | Dynamic range |
| `intensity_velocity_max` | dB/frame | Max intensity rate-of-change |
| `spectral_centroid_mean` | Hz | Mean spectral centroid |
| `spectral_tilt` | dB/kHz | Log-power spectrum slope |
| `mfcc_delta_mean` | — | Mean first-order MFCC delta |
| `zcr_mean` | — | Zero crossing rate |
| `teo_mean` | — | Mean Teager Energy Operator |
| `teo_std` | — | TEO standard deviation |
| `f1_mean` | Hz | Mean first formant |
| `f2_mean` | Hz | Mean second formant |
| `f3_mean` | Hz | Mean third formant |
| `formant_dispersion` | Hz | `(F3-F1)/2` — vocal tract length proxy |
| `npvi` | — | Normalised Pairwise Variability Index (0.0 pending MFA) |
| `articulation_rate` | syl/s | Syllable rate (0.0 pending MFA) |
| `emotion_score` | 0-1 | Composite vocal intensity score |
| `syllable_count_approx` | int | Vowel-count syllable proxy |

### Known Limitations

- **intensity_mean / intensity_max** — Mozilla normalises source audio to -20 dBFS.
  These columns are dead vectors. Cross-speaker intensity comparison is invalid.
- **jitter_local / shimmer_local** — MP3 codec degrades sub-ms glottal measurements.
  HNR and CPPS are more robust alternatives for this corpus.
- **npvi / articulation_rate** — Return 0.0 pending Phase 2 MFA phoneme alignment.
- **Tonal languages** — In Niger-Congo, Tai-Kadai, and Sino-Tibetan languages,
  `pitch_mean/std/range` measure lexical tone, not prosodic stress.

---

## Quality Tiers

| Tier | Label | SNR | C50 | Speech ratio |
|------|-------|-----|-----|--------------|
| 1 | PRISTINE | >= 35 dB | >= 35 dB | >= 0.30 |
| 2 | STUDIO | >= 25 dB | >= 20 dB | >= 0.30 |
| 3 | AMBIENT | >= 10 dB | any | >= 0.10 |
| 4 | TRASH | < 10 dB | any | < 0.10 |

---

## Usage Examples

```python
from datasets import load_dataset

# Load Indo-European family (default subset)
ds = load_dataset("moonscape-software/Human_Speech_Atlas", "Indo-European")
df = ds["train"].to_pandas()

# Cream clips only (T1+T2)
cream = df[df["sample_type"].str.startswith("cream", na=False)]

# Scripted (CV24) vs spontaneous (SPS2)
scripted    = df[df["corpus"] == "cv24"]
spontaneous = df[df["corpus"] == "sps2"]

# Cross-family pitch comparison (exclude tonal languages)
from datasets import load_dataset, concatenate_datasets
trees = ["Indo-European", "Austronesian", "Mesoamerican",
         "Eurasian-Minor", "Turkic", "Isolates"]
frames = [load_dataset("moonscape-software/Human_Speech_Atlas", t)["train"]
          for t in trees]
combined = concatenate_datasets(frames).to_pandas()
non_tonal = combined[~combined["lang_code"].isin(["th","cdo","cpx","brx"])]
print(non_tonal.groupby("lang_name")["pitch_mean"].mean().sort_values())
```

---

## Extraction Pipeline

**Pass 1 — Brouhaha** (Lavechin et al., Interspeech 2022) — SNR, C50, VAD, tier.

**Pass 2 — Classical Acoustic Features** — Parselmouth/Praat + librosa, 38 features.

**Pass 3 — MFA Phoneme Alignment** *(pending)* — Montreal Forced Aligner on cream
WAV sets. Will populate `npvi` and `articulation_rate`.

---

## Licensing

### Tier 1 — Moonscape Academic License (Non-Commercial)

Free for academic and non-commercial research on submission of institutional email.
Full terms in `LICENSE.md`. Key obligations:

- Cite Mozilla Common Voice and this dataset in any publications
- Never attempt to re-identify human speakers from acoustic features
- Never alter or remove forensic watermarks
- Not redistribute as a standalone commercial product

### Tier 2 / Tier 3 — Commercial License

Requires execution of a separate EULA with Moonscape Software prior to access.

| Source | License |
|--------|---------|
| Mozilla Common Voice CV24.0 | CC0-1.0 |
| Mozilla Spontaneous Speech SPS2.0 | CC0-1.0 |
| Feature extraction pipeline | Copyright Moonscape Software |

---

## Citation

```bibtex
@dataset{kleingertner2026hsa,
  author    = {Kleingertner, Chris},
  title     = {Moonscape Human Speech Atlas (HSA)},
  year      = {2026},
  publisher = {Moonscape Software},
  note      = {Multilingual acoustic prosody feature corpus across 90+ languages
               in 12 linguistic family trees. Companion to the Synthetic Speech Atlas.},
  url       = {https://huggingface.co/datasets/moonscape-software/Human_Speech_Atlas}
}

@misc{mozilla2024commonvoice,
  title  = {Mozilla Common Voice},
  author = {Mozilla Foundation},
  year   = {2024},
  url    = {https://commonvoice.mozilla.org},
  note   = {CV24.0 release, CC0-1.0}
}

@inproceedings{lavechin2022brouhaha,
  title     = {Brouhaha: Multi-task Training for Noise Speech Detection and Assessment},
  author    = {Lavechin, Marvin and others},
  booktitle = {Interspeech},
  year      = {2022}
}
```

---

## Access & Terms

This repository is **gated**. All users agree to:

1. Cite Mozilla Common Voice and this dataset in any publications
2. Never attempt to re-identify human speakers from acoustic features
3. Never alter, truncate, or remove the forensic watermarks (seeded FP16 noise)
4. Comply with upstream Mozilla Common Voice CC0 terms
5. Not redistribute this feature matrix as a standalone product without a
   separate commercial licence from Moonscape Software

**Tier 1 (Academic / Non-Commercial):** Approved on institutional email.
Full terms in `LICENSE.md`.

**Tier 2/3 (Commercial):** Requires EULA execution with Moonscape Software.

---

*Moonscape Software — Human Speech Atlas*
*Export version: HSA_v1_2026 | Watermark: HMAC-SHA256 seeded FP16 noise*