---
language:
  - tig
tags:
  - tigre
  - speech
  - audio-text
  - low-resource
license: cc-by-4.0
---

# Tigre Speech Corpus

## 1. Overview

This **Tigre Speech Corpus** is a curated collection of **18,470 aligned audio–text pairs** designed to support research and development in speech technologies for **Tigre (tig)**, an under-resourced South Semitic language spoken primarily in Eritrea. The dataset contains approximately **32 hours** of recorded speech contributed by **over 100 native speakers**.

It reflects a **collective effort** by Tigre-speaking contributors worldwide, including a significant number of **diaspora native speakers** who participated in the Mozilla Common Voice project. This corpus is intended to serve as a foundational resource for advancing NLP technologies for the Tigre language and is suitable for tasks such as:

- Automatic Speech Recognition (ASR)
- Forced alignment
- Speech translation
- Speech-to-text pretraining
- Low-resource speech benchmark creation

---

## 2. Data Source, Provenance, and Licensing

The data was voluntarily collected via the **Mozilla Common Voice** platform, with contributions from community members using personal devices (mobile phones and computers). The sentence prompts used for recording originate from the Common Voice sentence bank.

### Licensing

The dataset follows Mozilla Common Voice licensing terms:

- **Audio recordings (WAV files):** CC0 1.0 Universal — Public Domain Dedication  
- **Text content:** CC BY 4.0 — Attribution required  

---

## 3. Corpus Composition

### 3.1 Data Pairing Structure

Each item in the corpus consists of:

- A **`.wav` file** (audio recording)  
- A **`.txt` file** (transcript)  

Both share the same filename prefix (e.g., `clip_00123.wav` / `clip_00123.txt`), ensuring straightforward alignment.

### 3.2 Duration Distribution

The speech duration distribution:

- ~⅓ of audio clips: **< 5 seconds**  
- ~⅓ of audio clips: **5–7 seconds**  
- ~⅓ of audio clips: **7–41 seconds**  

This natural variation supports both short- and long-utterance modeling.

---

## 4. Dataset Structure and File Format

All files are stored in a flat directory structure inside the compressed release file.  
Each audio file has a **single matching transcript** with the exact same filename prefix.

### File Layout

```text
dataset_root/
├── clip_xxxxx.wav
├── clip_xxxxx.txt
├── clip_yyyyy.wav
├── clip_yyyyy.txt
└── ...
```

- **`.wav` files** contain audio recordings.  
- **`.txt` files** contain transcripts.  
- There are **no nested folders** to simplify ingestion by ASR pipelines.

### Naming Convention

Filename alignment pattern:

- `clip_12345.wav`  
- `clip_12345.txt`  

This ensures **1:1 audio–text alignment** for all 18,470 entries.

---

## 5. Intended Use & Applications

This dataset supports:

- **Low-resource ASR development**
- **End-to-end speech models** (wav2vec2, Whisper, MMS)
- **African language benchmarks**
- **Cross-lingual representation learning**
- **Phonetic/linguistic analysis**

Potential applications:

- Voice assistants  
- Speech-enabled educational tools  
- Accessibility technologies  
- Humanitarian language technology  

---

## 6. Ethical Considerations

- All recordings were contributed voluntarily.  
- Contributors acknowledged CC0 audio licensing.  
- No personally identifiable information (PII) is included.  
- Derivative models should respect the spirit of open, community-driven data.

---

## 7. Recommended Citation

```
@dataset{tigre_speech_corpus_2025,
  title = {Tigre Speech Corpus},
  author = {Tigre Diaspora Community Contributors and Mozilla Common Voice},
  year = {2025},
  url = {https://huggingface.co/},
  note = {A collection of 18,470 audio–text pairs for the Tigre language.}
}
```

---

## 8. Acknowledgments

We gratefully acknowledge:

- The **Tigre diaspora community** for their contributions.  
- The **Mozilla Common Voice** team for enabling community-driven speech data creation.