Add dataset card

README.md

@@ -1,95 +1,168 @@
 ---
-dataset_info:
-  features:
-  - name: audio
-    dtype:
-      audio:
-        sampling_rate: 16000
-  - name: duration_s
-    dtype: float64
-  - name: sample_rate
-    dtype: int64
-  - name: language_iso
-    dtype: string
-  - name: language_name
-    dtype: string
-  - name: language_family
-    dtype: string
-  - name: dialect
-    dtype: string
-  - name: country
-    dtype: string
-  - name: region
-    dtype: string
-  - name: gloss_en
-    dtype: string
-  - name: transcription_seke
-    dtype: string
-  - name: phonemes_ipa
-    dtype: string
-  - name: is_swadesh
-    dtype: bool
-  - name: swadesh_number
-    dtype: int64
-  - name: is_alternative_form
-    dtype: bool
-  - name: grammatical_categories
-    dtype: string
-  - name: source_identifier
-    dtype: string
-  - name: source_title
-    dtype: string
-  - name: source_filename
-    dtype: string
-  - name: linguistic_type
-    dtype: string
-  - name: recording_date
-    dtype: string
-  - name: recording_location
-    list: string
-  - name: speaker_name
-    dtype: string
-  - name: researcher_name
-    dtype: string
-  - name: project
-    dtype: string
-  - name: source_collection
-    dtype: string
-  - name: source_url
-    dtype: string
-  - name: license
-    dtype: string
-  - name: quality_tier
-    dtype: string
-  - name: snr_db
-    dtype: float64
-  - name: loudness_lufs
-    dtype: float64
-  - name: whisper_detected_lang
-    dtype: string
-  - name: whisper_avg_logprob
-    dtype: float64
-  - name: whisper_no_speech_prob
-    dtype: float64
-  splits:
-  - name: train
-    num_bytes: 32231280.0
-    num_examples: 741
-  - name: validation
-    num_bytes: 4087726.0
-    num_examples: 93
-  - name: test
-    num_bytes: 3771877.0
-    num_examples: 93
-  download_size: 38783321
-  dataset_size: 40090883.0
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: validation
-    path: data/validation-*
-  - split: test
-    path: data/test-*
+license: cc-by-4.0
+language:
+- skj
+task_categories:
+- automatic-speech-recognition
+- audio-classification
+task_ids:
+- speech-recognition
+pretty_name: Seke (SKJ) Language Corpus — Endangered Language Alliance
+size_categories:
+- n<1K
+tags:
+- endangered-language
+- seke
+- nepal
+- sino-tibetan
+- low-resource
+- linguistics
+- audio
+- field-recording
+- whisper
+- wav2vec2
 ---
+
+# 🏔️ Seke (SKJ) Language Dataset
+## Endangered Language Alliance × Internet Archive
+
+> **Seke** (`skj`) is a critically endangered Sino-Tibetan language spoken by approximately 700 people
+> in the five villages of Upper Mustang district, Nepal, and in diaspora communities in New York City.
+> This dataset represents one of the most complete public audio corpora of Seke ever assembled.
+> Dataset created by Anil Tamang (himalaya-ai).
+---
+
+## 📊 Dataset Statistics
+
+| Metric | Value |
+|--------|-------|
+| Total audio clips | 927 |
+| Total duration | 20.5 minutes |
+| Number of speakers | 3 |
+| Sample rate | 16000 Hz |
+| Format | 16-bit PCM WAV (mono) |
+| Language ISO | `skj` |
+| Date range | 2018–2021 |
+| Assembled | 2026-04-23 |
+
+### Quality Tier Distribution
+
+| Tier | Count | Description |
+|------|-------|-------------|
+| A | 46 | Gold: elicited clips, controlled studio recording, short utterances (<10s), SNR>20dB |
+| B | 437 | Silver: field recordings, good quality, longer utterances |
+| C | 444 | Bronze: field recordings with background noise, or long sessions |
+
+### Linguistic Type Distribution
+
+| Language Description | 681 |
+| Lexicon | 246 |
+
+
+---
+
+## 🔤 Language Information
+
+- **ISO 639-3**: `skj`
+- **Family**: Sino-Tibetan → Tibeto-Burman → Bodish
+- **Dialect**: Primarily Chhusang (Tshugsang) dialect
+- **Typology**: Verb-final word order, ergative alignment, evidential marking
+- **Script**: No standardized orthography (romanized transcriptions in this dataset)
+- **Endangerment**: Critically endangered (~700 speakers)
+- **Region**: Upper Mustang, Gandaki Province, Nepal; NYC diaspora
+
+---
+
+## 🗂️ Dataset Fields
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `audio` | Audio | 16kHz mono WAV, trimmed and normalized |
+| `duration_s` | float | Duration in seconds |
+| `gloss_en` | string | English translation/gloss (from ELA elicitation) |
+| `transcription_seke` | string | Whisper ASR output (romanized approximation) |
+| `phonemes_ipa` | string | IPA phonemes from Allosaurus (where available) |
+| `grammatical_categories` | string | Comma-separated grammatical category tags |
+| `linguistic_type` | string | OLAC type: Lexicon / Language Description / Primary Text |
+| `quality_tier` | string | A/B/C quality tier |
+| `speaker_name` | string | Speaker name |
+| `recording_date` | string | Session date |
+| `source_identifier` | string | Internet Archive item identifier |
+| `source_url` | string | Direct link to IA item |
+| `is_swadesh` | bool | Part of Swadesh list elicitation |
+| `swadesh_number` | int | Swadesh list number (-1 if not applicable) |
+| `is_alternative_form` | bool | Alternative pronunciation of same sentence |
+| `snr_db` | float | Signal-to-noise ratio in dB |
+| `loudness_lufs` | float | Original LUFS loudness (pre-normalization) |
+
+---
+
+## 🚀 Usage
+
+```python
+from datasets import load_dataset
+
+# Load full dataset
+ds = load_dataset("Titung/seke-nepali-dataset")
+
+# Load only high-quality elicited clips (Tier A)
+ds_gold = load_dataset("Titung/seke-nepali-dataset", split="train")
+ds_gold = ds_gold.filter(lambda x: x["quality_tier"] == "A")
+
+# Fine-tune Whisper on Seke
+from transformers import WhisperForConditionalGeneration, WhisperProcessor
+model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-large-v3")
+processor = WhisperProcessor.from_pretrained("openai/whisper-large-v3")
+
+# Prepare features
+def prepare_dataset(batch):
+    audio = batch["audio"]
+    batch["input_features"] = processor(
+        audio["array"], sampling_rate=audio["sampling_rate"],
+        return_tensors="pt"
+    ).input_features[0]
+    batch["labels"] = processor.tokenizer(
+        batch["gloss_en"]
+    ).input_ids
+    return batch
+
+ds_prepared = ds["train"].map(prepare_dataset)
+```
+
+---
+
+## 📖 Source & Attribution
+
+All audio data sourced from the **Endangered Language Alliance (ELA)** archive on Internet Archive:
+- Collection: https://archive.org/details/elalliance
+- ELA website: https://www.elalliance.org
+- Primary researcher: **Ross Perlin**, Co-Director, ELA
+- Primary speakers: **Rasmina Gurung**, **Nora Gurung**, and others
+- Recorded 2018–2021 at Columbia University and in Upper Mustang, Nepal
+- Supported in part by the National Endowment for the Humanities
+
+Original data archived under **Creative Commons Attribution 4.0** (CC-BY-4.0).
+This dataset derivative is also released under **CC-BY-4.0**.
+Please cite ELA and the original depositors in any academic use.
+
+### Suggested Citation
+```
+Endangered Language Alliance. (2021). Seke (SKJ) Language Recordings.
+Internet Archive. https://archive.org/details/elalliance
+
+Dataset assembled by [Anil Tamang/himalaya-ai] (2026).
+Available at: https://huggingface.co/datasets/Titung/seke-nepali-dataset
+```
+
+---
+
+## ⚠️ Important Notes
+
+1. **Transcriptions are approximate**: The `transcription_seke` field contains Whisper ASR output
+   on an unseen language — treat as a phonetic approximation, not verified orthography.
+   Manual validation by a Seke speaker is strongly recommended.
+2. **No standardized orthography**: Seke has no official writing system. Romanizations may vary.
+3. **Ethical use**: This data documents a critically endangered language. Please use it to
+   support language preservation, not for commercial exploitation.
+4. **Contact ELA**: For research partnerships or access to additional materials:
+   https://www.elalliance.org/contact