| | --- |
| | language: |
| | - zh |
| | - en |
| | license: cc-by-nc-4.0 |
| | task_categories: |
| | - automatic-speech-recognition |
| | tags: |
| | - code-switching |
| | dataset_info: |
| | config_names: |
| | - SECoMiCSC |
| | - DevCECoMiCSC |
| | --- |
| | # Robust Code-Switching ASR Benchmark |
| |
|
| | ## Dataset Summary |
| | This dataset is a **processed and cleaned derivative** of the open-source MagicData corpus, specifically optimized for our project **Code-Switched ASR robustness** (e.g., Whisper fine-tuning). |
| |
|
| | We addressed the "context fragmentation" issue in original long-form audio by applying a **Smart-Merge Strategy** (merging short segments into 5-15s chunks using ground-truth timestamps) and filtering out conversational fillers. |
| |
|
| | ## Original Data Sources |
| | This dataset is derived from the following open-source datasets released by **MagicData Technology**: |
| |
|
| | * **Training Subset:** Derived from **ASR-SECoMiCSC** |
| | * *Source:* [MagicData Open Source Community](https://magichub.com/datasets/chinese-english-code-mixing-conversational-speech-corpus/) |
| | * **Benchmark/Test Subset:** Derived from **ASR-DevCECoMiCSC** |
| | * *Source:* [MagicData Open Source Community](https://magichub.com/datasets/dev-set-of-chinese-english-code-mixing-conversational-speech-corpus/) |
| |
|
| | *> Note: This repository contains processed audio chunks and metadata only. Please refer to the original links for full datasets and license details.* |
| |
|
| | ## Processing Pipeline (Why this version?) |
| | 1. **Smart Segmentation:** Instead of random VAD cutting, we merged short utterances into **5s - 15s segments** based on speaker identity and time gaps. This provides better context for Transformer-based models. |
| | 2. **Noise Filtering:** Removed pure filler segments (e.g., "嗯", "啊", "[ENS]") to reduce hallucination during training. |
| |
|
| | ## Usage |
| |
|
| | ```python |
| | from datasets import load_dataset |
| | |
| | # 1. Load Training Data (SECoMiCSC) |
| | dataset_train = load_dataset("1uckyan/code-switch_chunks", data_dir="SECoMiCSC", split="train") |
| | |
| | # 2. Load Benchmark Test Set (DevCECoMiCSC) |
| | dataset_test = load_dataset("1uckyan/code-switch_chunks", data_dir="DevCECoMiCSC", split="train") |
