README
WSYue-ASR-eval: Cantonese ASR Benchmark
To address the unique linguistic characteristics of Cantonese in speech recognition, we propose WSYue-ASR-eval, a benchmark specifically designed for evaluating Cantonese ASR systems. It is tailored to assess model performance across diverse lengths, domains, and linguistic phenomena of Cantonese speech.
The test set annotations are provided by Beijing AISHELL Technology Co., Ltd.
Key features:
- Annotated through multiple rounds of manual labeling
- Includes rich tags such as text transcription, emotion, age, and gender
- Covers Cantonese-English code-switching and multi-domain conditions
- Enables comprehensive evaluation across varying speech lengths
WSYue-ASR-eval Subsets
| Set | Duration | Speakers | Hours |
|---|---|---|---|
| Short | 0–10 s | 2861 | 9.46 |
| Long | 10–30 s | 838 | 1.97 |
Total: 11.4 hours, with diverse speakers and scenarios.
Contributors
17 commits
Similar repos
README
WSYue-ASR-eval: Cantonese ASR Benchmark
To address the unique linguistic characteristics of Cantonese in speech recognition, we propose WSYue-ASR-eval, a benchmark specifically designed for evaluating Cantonese ASR systems. It is tailored to assess model performance across diverse lengths, domains, and linguistic phenomena of Cantonese speech.
The test set annotations are provided by Beijing AISHELL Technology Co., Ltd.
Key features:
- Annotated through multiple rounds of manual labeling
- Includes rich tags such as text transcription, emotion, age, and gender
- Covers Cantonese-English code-switching and multi-domain conditions
- Enables comprehensive evaluation across varying speech lengths
WSYue-ASR-eval Subsets
| Set | Duration | Speakers | Hours |
|---|---|---|---|
| Short | 0–10 s | 2861 | 9.46 |
| Long | 10–30 s | 838 | 1.97 |
Total: 11.4 hours, with diverse speakers and scenarios.
Similar repos
Linked in READMEs
Contributors
17 commits