---
language:
- nre
license: cc-by-4.0
task_categories:
- automatic-speech-recognition
pretty_name: "NE ASR Augmented Dataset -- Rengma (nre)"
tags:
- augmented
- ne-india
- low-resource
- speech
- asr
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train/*.parquet
      - split: validation
        path: data/validation/*.parquet
      - split: test
        path: data/test/*.parquet
---

# NE ASR Augmented Dataset -- Rengma (nre)

Augmented automatic speech recognition dataset for **Rengma** (`nre`),
a Tibeto-Burman language spoken in Nagaland, India.

## Source

Augmented from [`sulabhkatiyar/ne-asr-nre`](https://huggingface.co/datasets/sulabhkatiyar/ne-asr-nre)
(original transcribed speech data from the [ARTPARK-IISc Vaani project](https://vaani.iisc.ac.in/)).

## Language Information

| Property | Value |
|----------|-------|
| Language | Rengma |
| ISO 639-3 | `nre` |
| Family | Tibeto-Burman |
| Region | Nagaland, India |
| Tonal | Yes |
| Tier | B (0.51h original data) |

## Dataset Statistics

- **Original training samples**: 336
- **Augmented training samples**: 1,008 (3x augmentation)
- **Train shards**: 2
- **Estimated original duration**: ~0.5 hours
- **Estimated augmented duration**: ~1.5 hours

| Split | Samples |
|-------|--------:|
| train | 1,008 |
| validation | 11 |
| test | 28 |

## Transformations Applied

Each original training sample produces **3 samples** (1 original + 2 speed + 0 pitch):

- **Speed perturbation**: 0.9x, 1.1x (2 variants per sample)
- **Pitch shift**: Disabled (tonal language -- pitch shift would alter lexical meaning)
- **Noise augmentation**: Not applied

### SpecAugment Parameters (for training, NOT in this dataset)

These parameters are consumed by the training script and are **not** baked into the audio files:

- `mask_time_prob`: 0.05
- `mask_time_length`: 10
- `mask_feature_prob`: 0.03
- `mask_feature_length`: 10
- `layerdrop`: 0.05

Full augmentation config: [`configs/augmentation_config.yaml`](https://github.com/sulabhkatiyar/ne_asr/blob/main/configs/augmentation_config.yaml)

## Dataset Format

- **Audio**: 16kHz mono WAV (stored as Parquet with audio bytes)
- **Text**: Transcriptions
- **Features**: `audio`, `text`, `language`, `augmentation`
- **Augmentation labels**: `original`, `speed_0.9`, `speed_1.1`

## How to Use

```python
from datasets import load_dataset

# Load the full dataset
ds = load_dataset("sulabhkatiyar/ne-asr-nre-aug")

# Load only the training split
train = load_dataset("sulabhkatiyar/ne-asr-nre-aug", split="train")

# Filter to only original (non-augmented) samples
original_only = train.filter(lambda x: x["augmentation"] == "original")

# Filter to a specific augmentation type
speed_09 = train.filter(lambda x: x["augmentation"] == "speed_0.9")
```

## Original Data

- Source dataset: [`sulabhkatiyar/ne-asr-nre`](https://huggingface.co/datasets/sulabhkatiyar/ne-asr-nre)
- Project: [ARTPARK-IISc Vaani](https://vaani.iisc.ac.in/)
- License: CC-BY-4.0

## Citation

If you use this dataset, please cite the Vaani project and acknowledge the augmentation pipeline.