---
language:
- mn
license: cc-by-4.0
task_categories:
- automatic-speech-recognition
task_ids: []
pretty_name: "FLEURS — Mongolian (Clean)"
tags:
- mongolian
- speech
- audio
- fleurs
---

# FLEURS — Mongolian (Quality-Filtered)

A quality-filtered version of the [FLEURS](https://huggingface.co/datasets/google/fleurs) (`mn_mn`) Mongolian benchmark dataset, cleaned for use with [oron-tts](https://github.com/btseee/oron-tts) (F5-TTS / Flow Matching).

## Source

Derived from `google/fleurs` config `mn_mn`. FLEURS is the speech version of the FLoRes machine translation benchmark, covering 2,009 n-way parallel sentences across 102 languages.

## Cleaning Pipeline

6-stage automated quality filter, thresholds calibrated for Mongolian TTS training (low-resource language; DeepFilterNet denoising applied downstream in oron-tts):

| Stage | Method | Threshold |
|---|---|---|
| 1. Format normalization | librosa | mono · 16 kHz |
| 2. Voice activity detection | Silero VAD | ≥25 % speech frames |
| 3. SNR filter | RMS-based SNR | ≥8 dB |
| 4. Pitch metadata | CREPE F0 | recorded when available; not a rejection gate |
| 5. AI quality score | DNSMOS P.835 | OVR ≥2.2 · SIG ≥2.4 · BAK ≥2.0 |
| 6. Full sentence verification | Whisper large-v3 + CER | CER ≤0.35, or ≤0.50 when length ratio is 0.75–1.25 |

Ground truth for sentence verification: `raw_transcription` field.
Clips are kept between **1–30 seconds** to match oron-tts training limits. All passing clips are peak-normalized to −1 dBFS and resampled to **24 kHz**.

## Schema

All original FLEURS fields preserved, plus computed quality metrics:

| Field | Type | Description |
|---|---|---|
| `id` | int32 | Sample ID |
| `num_samples` | int32 | Number of audio samples |
| `path` | string | Audio file path |
| `audio` | Audio(24000) | Cleaned audio resampled to 24 kHz |
| `raw_transcription` | string | Original (unnormalized) transcription |
| `transcription` | string | Normalized transcription |
| `gender` | int32 | Speaker gender class |
| `lang_id` | int32 | Language class ID |
| `language` | string | Language name |
| `lang_group_id` | int32 | Language group class ID |
| `snr_db` | float32 | SNR in dB |
| `mean_f0_hz` | float32 | Mean F0 (Hz) |
| `pitch_confidence` | float32 | CREPE pitch confidence |
| `dnsmos_sig` | float32 | DNSMOS signal quality |
| `dnsmos_bak` | float32 | DNSMOS background noise |
| `dnsmos_ovr` | float32 | DNSMOS overall MOS |
| `dnsmos_p808` | float32 | DNSMOS P.808 MOS |
| `cer` | float32 | CER vs. raw_transcription |
| `asr_transcript` | string | Whisper large-v3 output |
| `duration_s` | float32 | Duration in seconds |

## Usage

```python
from datasets import load_dataset
ds = load_dataset("btsee/fleurs-mn")
sample = ds["train"][0]
```

## License

[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)