Zhipu Asr
by @franklu0819-lang
Automatic Speech Recognition (ASR) using Zhipu AI (BigModel) GLM-ASR model. Use when you need to transcribe audio files to text. Supports Chinese audio trans...
clawhub install zhipu-asr📖 About This Skill
name: zhipu-asr description: Automatic Speech Recognition (ASR) using Zhipu AI (BigModel) GLM-ASR model. Use when you need to transcribe audio files to text. Supports Chinese audio transcription with context prompts, custom hotwords, and multiple audio formats. metadata: { "openclaw": { "requires": { "bins": ["jq", "curl", "ffmpeg"], "env": ["ZHIPU_API_KEY"] }, }, }
Zhipu AI Automatic Speech Recognition (ASR)
Transcribe Chinese audio files to text using Zhipu AI's GLM-ASR model.
Setup
1. Get your API Key: Get a key from Zhipu AI Console
2. Set it in your environment:
export ZHIPU_API_KEY="your-key-here"
Supported Audio Formats
> Note: The script automatically converts unsupported formats to MP3 using ffmpeg. Only WAV and MP3 are accepted by the API, but you can use any format that ffmpeg supports.
File Constraints
Usage
Basic Transcription
Transcribe an audio file with default settings:
bash scripts/speech_to_text.sh recording.wav
Transcription with Context
Provide previous transcription or context for better accuracy:
bash scripts/speech_to_text.sh recording.wav "这是之前的转录内容，有助于提高准确性"
Transcription with Hotwords
Use custom vocabulary to improve recognition of specific terms:
bash scripts/speech_to_text.sh recording.mp3 "" "人名,地名,专业术语,公司名称"
Full Options
Combine context and hotwords:
bash scripts/speech_to_text.sh recording.wav "会议记录片段" "张三,李四,项目名称"
Parameters:
audio_file (required): Path to audio file (.wav or .mp3)prompt (optional): Previous transcription or context text (max 8000 chars)hotwords (optional): Comma-separated list of specific terms (max 100 words)Features
Context Prompts
Why use context prompts:
When to use:
Example:
bash scripts/speech_to_text.sh part2.wav "第一部分的转录内容：讨论了项目进展和下一步计划"
Hotwords
What are hotwords: Custom vocabulary list that boosts recognition accuracy for specific terms.
Best use cases:
Examples:
# Medical transcription
bash scripts/speech_to_text.sh medical.wav "" "患者,症状,诊断,治疗方案"Business meeting
bash scripts/speech_to_text.sh meeting.wav "" "张经理,李总,项目代号,预算"Tech discussion
bash scripts/speech_to_text.sh tech.wav "" "API,数据库,算法,框架"
Workflow Examples
Transcribe a Meeting
# Part 1
bash scripts/speech_to_text.sh meeting_part1.wavPart 2 with context
bash scripts/speech_to_text.sh meeting_part2.wav "第一部分讨论了项目进度" "张总,李经理,项目名称"Part 3 with context
bash scripts/speech_to_text.sh meeting_part3.wav "前两部分讨论了项目进度和预算" "张总,李经理,项目名称"
Transcribe a Lecture
bash scripts/speech_to_text.sh lecture.wav "" "教授,课程名称,专业术语1,专业术语2"
Process Multiple Files
for file in recording_*.wav; do
bash scripts/speech_to_text.sh "$file"
done
Audio Quality Tips
Best practices for accurate transcription:
1. Clear audio source - Minimize background noise - Use good quality microphone - Speak clearly and at moderate pace
2. Optimal audio settings - Sample rate: 16000 Hz or higher - Bit depth: 16-bit or higher - Single channel (mono) is sufficient
3. File preparation - Remove silence from beginning/end - Normalize audio levels - Ensure consistent volume
Output Format
The script outputs JSON with:
id: Task IDcreated: Request timestamp (Unix timestamp)request_id: Unique request identifiermodel: Model name usedtext: Transcribed textExample output:
{
"id": "task-12345",
"created": 1234567890,
"request_id": "req-abc123",
"model": "glm-asr-2512",
"text": "你好，这是转录的文本内容"
}
Troubleshooting
File Size Issues:
Duration Issues:
Poor Accuracy:
Format Issues:
Limitations
Performance Notes
💡 Examples
Basic Transcription
Transcribe an audio file with default settings:
bash scripts/speech_to_text.sh recording.wav
Transcription with Context
Provide previous transcription or context for better accuracy:
bash scripts/speech_to_text.sh recording.wav "这是之前的转录内容，有助于提高准确性"
Transcription with Hotwords
Use custom vocabulary to improve recognition of specific terms:
bash scripts/speech_to_text.sh recording.mp3 "" "人名,地名,专业术语,公司名称"
Full Options
Combine context and hotwords:
bash scripts/speech_to_text.sh recording.wav "会议记录片段" "张三,李四,项目名称"
Parameters:
audio_file (required): Path to audio file (.wav or .mp3)prompt (optional): Previous transcription or context text (max 8000 chars)hotwords (optional): Comma-separated list of specific terms (max 100 words)⚙️ Configuration
1. Get your API Key: Get a key from Zhipu AI Console
2. Set it in your environment:
export ZHIPU_API_KEY="your-key-here"
📋 Tips & Best Practices
File Size Issues:
Duration Issues:
Poor Accuracy:
Format Issues: