---
license: other
task_categories:
- automatic-speech-recognition
- translation
language:
- nan
- zh
tags:
- minspeech
- hokkien
- s2tt
- dataset-processing
pretty_name: MinSpeech Cleaned (Private Research Fork)
---

# MinSpeech: Cleaned Multi-dialect Min-nan Dataset (Private)

## Important Legal Notice & Copyright Status

This repository is a **Private Research Fork** of the MinSpeech corpus. It is maintained strictly for individual research purposes, specifically for fine-tuning **Automatic Speech Recognition (ASR)** and **Speech-to-Text Translation (S2TT)** models.

### 1. Ownership & Licensing
* **Annotations & Metadata:** The transcriptions and segment metadata are derived from the MinSpeech project ([Interspeech 2024](https://doi.org/10.21437/Interspeech.2024-2414)). These elements are used under the **CC BY-NC-SA 4.0** license.
* **Audio Content:** We **do not claim ownership** of the audio data. All audio files are sourced from public YouTube content. The copyright for the raw audio remains entirely with the **original content creators (YouTube uploaders)**.
* **Usage Intent:** This data is processed and stored here solely for non-commercial, non-expressive machine learning training. No audio data is intended for redistribution or public performance.

### 2. Fair Use & Compliance Statement
Following the copyright regulations of Mainland China, Taiwan, the US, and Australia regarding AI research:
* **Non-Infringement:** This repository does not seek to infringe upon the rights of the original creators. By keeping this repository **Private**, we ensure that no unauthorized public distribution of copyrighted audio occurs.
* **Transformation:** The audio is utilized to extract statistical linguistic features for S2TT/ASR model weights, which is considered a transformative, non-consumptive use under research exemptions.

---

## Dataset Description

This private version contains cleaned and pre-processed samples from the MinSpeech corpus to optimize training efficiency.

* **Original Paper:** *MinSpeech: A Corpus of Southern Min Dialect for Automatic Speech Recognition* (Lin et al., 2024).
* **Modifications:** * Audio standardized to 16kHz Mono WAV.
    * VAD-based silence removal and noise reduction.
    * Alignment verified between YouTube segments and transcriptions.

---

## License and Usage Restrictions

This private dataset repository contains a compilation of data from multiple sources with different licensing terms. 

### 1. Annotations & Metadata (CC BY-NC-SA 4.0)
The text transcriptions, timestamps, and translation labels are derived from the **MinSpeech** project. 
* These elements are strictly governed by the **Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International** license. 
* Any redistribution of these specific metadata files must adhere to this license.

### 2. Audio Data (Original Creator Copyright)
The audio files in this repository are processed derivatives of public content from **YouTube**. 
* **No License Granted:** We do not hold the copyright to these audio recordings and cannot grant any license for their use.
* **Third-Party Rights:** Copyright remains with the original YouTube content creators.
* **Research Exception:** This data is stored here in a **Private** capacity for non-commercial machine learning research (Fine-tuning ASR/S2TT models) under "Fair Use" or "Research/Study" exemptions as defined in relevant jurisdictions (Mainland China, Taiwan, US, Australia).

### 3. Usage Policy
By accessing this private repository, you agree that:
1. You will not redistribute the audio files.
2. You will use this data solely for non-commercial academic research.
3. You acknowledge that the model trained on this data (ASR/S2TT) is a statistical representation and does not contain the original audio.