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

wenet_speech

Dataset ID

lmms-lab/WenetSpeech

Paper

N/A

Tags

Audio, SpeechRecognition

Metrics

mer

Default Shots

0-shot

Evaluation Split

test_meeting

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

dev

13,825

161

161

161

test_meeting

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)