| --- |
| license: other |
| license_name: all-rights-reserved |
| language: |
| - ar |
| - en |
| - es |
| - he |
| - hi |
| - ja |
| - ko |
| task_categories: |
| - text-to-speech |
| - automatic-speech-recognition |
| tags: |
| - audio |
| - speech |
| - tts |
| - multilingual |
| - luel |
| size_categories: |
| - n<1K |
| modality: |
| - audio |
| pretty_name: Luel Multilingual TTS Samples |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: metadata.csv |
| --- |
| |
| # Multilingual TTS Samples (Luel) |
|
|
| **License:** All Rights Reserved. Proprietary. Access only for authorized parties; no redistribution or use without permission. See [LICENSE](LICENSE). |
|
|
| A multilingual text-to-speech / read-speech dataset of short scripted utterances across 7 languages. Each sample is a single-speaker recording of a written prompt, paired with rich speaker and recording metadata. Useful for TTS training and evaluation, ASR adaptation, dialect/accent studies, and read-speech benchmarking. |
|
|
| --- |
|
|
| ## Quick Stats |
|
|
| | Metric | Value | |
| |--------|-------| |
| | Languages | 7 (English, Hindi, Japanese, Arabic, Korean, Hebrew, Spanish) | |
| | Total samples | 685 | |
| | Total duration | 2h 20m (8,428 s) | |
| | Total words | 13,707 | |
| | Mean duration | 12.3 s | |
| | Audio format | WAV | |
| | Speaker metadata | gender, dialect, mother tongue, birth place, year of birth, language proficiencies | |
|
|
| ### Per-Language Breakdown |
|
|
| | Language | Code | Samples | Duration | Words | |
| |----------|------|---------|----------|-------| |
| | Hindi | hi | 211 | 48m 31s | 5,782 | |
| | English | en | 199 | 31m 48s | 4,299 | |
| | Japanese | ja | 163 | 38m 55s | 1,597 | |
| | Arabic | ar | 51 | 10m 22s | 1,054 | |
| | Korean | ko | 40 | 7m 05s | 486 | |
| | Hebrew | he | 11 | 1m 54s | 231 | |
| | Spanish | es | 10 | 1m 53s | 258 | |
|
|
| Full per-language stats (gender breakdown, per-dialect counts) are in [`stats.json`](stats.json). |
|
|
| --- |
|
|
| ## Structure |
|
|
| ``` |
| audio/ |
| ar/ ar_00001.wav … ar_00051.wav |
| en/ en_00001.wav … en_00199.wav |
| es/ es_00001.wav … es_00010.wav |
| he/ he_00001.wav … he_00011.wav |
| hi/ hi_00001.wav … hi_00211.wav |
| ja/ ja_00001.wav … ja_00163.wav |
| ko/ ko_00001.wav … ko_00040.wav |
| metadata.csv |
| stats.json |
| LICENSE |
| README.md |
| ``` |
|
|
| The dataset follows the Hugging Face `audiofolder` layout: `metadata.csv` carries one row per audio file, with `file_name` referencing the WAV at `audio/{lang_code}/{id}.wav`. |
|
|
| --- |
|
|
| ## Loading |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset( |
| "Luel-ai/luel-multilingual-tts-samples", |
| split="train", |
| ) |
| print(ds[0]) |
| ``` |
|
|
| Filter by language: |
|
|
| ```python |
| en = ds.filter(lambda x: x["language_code"] == "en") |
| ``` |
|
|
| --- |
|
|
| ## Metadata Schema |
|
|
| Each row in `metadata.csv` contains: |
|
|
| | Field | Type | Description | |
| |-------|------|-------------| |
| | `file_name` | string | Relative path to audio (`audio/{code}/{id}.wav`) | |
| | `id` | string | Sample id (`{lang_code}_{NNNNN}`) | |
| | `language` | string | Spoken language (e.g. `English`) | |
| | `language_code` | string | ISO 639-1 code (`en`, `hi`, `ja`, `ar`, `ko`, `he`, `es`) | |
| | `script` | string | Text the speaker read | |
| | `type_of_script` | string | Prompt type (e.g. `monologues`) | |
| | `duration_seconds` | float | Audio duration in seconds | |
| | `gender` | string | Speaker gender | |
| | `ethnicity` | string | Speaker self-reported ethnicity (may be empty) | |
| | `birth_place` | string | Speaker country of birth | |
| | `mother_tongue` | string | Speaker native language | |
| | `dialect` | string | Speaker dialect / regional variety | |
| | `year_of_birth` | int | Speaker year of birth | |
| | `years_at_birth_place` | int | Years lived at birth place | |
| | `languages_data` | json | Spoken languages with proficiency levels (JSON-encoded) | |
| | `recording_environment` | string | Environment label (`home`, etc.) | |
| | `os` | string | Recording OS | |
| | `device` | string | Device type | |
| | `browser` | string | Browser used | |
|
|
| --- |
|
|
| ## Intended Uses |
|
|
| - TTS / voice cloning training and evaluation |
| - Multilingual ASR fine-tuning, especially for low-resource accents and dialects |
| - Speaker / dialect classification benchmarks |
| - Read-speech / prosody research |
|
|
| ## Out-of-Scope Uses |
|
|
| - Identifying or re-contacting speakers |
| - Any use prohibited by the LICENSE |
|
|
| --- |
|
|
| ## Access |
|
|
| This repository is gated. You must accept the conditions to access files and content. For access requests, contact Luel (https://luel.ai). |
|
|
