WenetSpeech#
Overview#
WenetSpeech is a large-scale Mandarin Chinese speech corpus with over 10,000 hours of multi-domain transcribed audio data, designed for speech recognition research.
Task Description#
Task Type: Automatic Speech Recognition (ASR)
Input: Audio recordings with Mandarin Chinese speech
Output: Transcribed text in Chinese
Domain: Multi-domain (internet, meeting)
Key Features#
Large-scale Mandarin Chinese speech corpus (10,000+ hours)
Multi-domain coverage: internet content, meetings
High-quality transcriptions
Suitable for evaluating Chinese ASR systems
Supports mixed Chinese-English text evaluation
Evaluation Notes#
Default configuration uses test_meeting split
Subsets by domain: dev (development), test_meeting (meeting domain)
Primary metric: MER (Mixed Error Rate)
MER tokenizes Chinese characters individually and English words as whole tokens
Prompt: “Please listen to the audio and transcribe what you hear”
Properties#
Property |
Value |
|---|---|
Benchmark Name |
|
Dataset ID |
|
Paper |
N/A |
Tags |
|
Metrics |
|
Default Shots |
0-shot |
Evaluation Split |
|
Data Statistics#
Metric |
Value |
|---|---|
Total Samples |
22,195 |
Prompt Length (Mean) |
161 chars |
Prompt Length (Min/Max) |
161 / 161 chars |
Per-Subset Statistics:
Subset |
Samples |
Prompt Mean |
Prompt Min |
Prompt Max |
|---|---|---|---|---|
|
13,825 |
161 |
161 |
161 |
|
8,370 |
161 |
161 |
161 |
Audio Statistics:
Metric |
Value |
|---|---|
Total Audio Files |
22,195 |
Audio per Sample |
min: 1, max: 1, mean: 1 |
Formats |
wav |
Sample Example#
Subset: dev
{
"input": [
{
"id": "c30c80b4",
"content": [
{
"text": "Please listen to the audio and transcribe what you hear. Please only provide the transcription without any additional commentary. Do not include any punctuation."
},
{
"audio": "[BASE64_AUDIO: wav, ~175.3KB]",
"format": "wav"
}
]
}
],
"target": "对我做了介绍啊那么我想说的是呢大家如果对我的研究感兴趣呢嗯",
"id": 0,
"group_id": 0,
"metadata": {
"text": "对我做了介绍啊那么我想说的是呢大家如果对我的研究感兴趣呢嗯"
}
}
Prompt Template#
Prompt Template:
Please listen to the audio and transcribe what you hear. Please only provide the transcription without any additional commentary. Do not include any punctuation.
Usage#
Using CLI#
evalscope eval \
--model YOUR_MODEL \
--api-url OPENAI_API_COMPAT_URL \
--api-key EMPTY_TOKEN \
--datasets wenet_speech \
--limit 10 # Remove this line for formal evaluation
Using Python#
from evalscope import run_task
from evalscope.config import TaskConfig
task_cfg = TaskConfig(
model='YOUR_MODEL',
api_url='OPENAI_API_COMPAT_URL',
api_key='EMPTY_TOKEN',
datasets=['wenet_speech'],
dataset_args={
'wenet_speech': {
# subset_list: ['dev', 'test_meeting'] # optional, evaluate specific subsets
}
},
limit=10, # Remove this line for formal evaluation
)
run_task(task_cfg=task_cfg)