About Prompt
- Prompt Type – Dynamic
- Prompt Platform – ChatGPT, Grok, Deepseek, Gemini, Copilot, Midjourney, Meta AI and more
- Niche – Specific AI Tools
- Language – English
- Category – Speech Recognition
- Prompt Title – AI Prompt for Voice-to-Text
Prompt Details
This prompt is designed to be adaptable across various AI platforms for speech recognition and transcription tasks. It utilizes dynamic variables to maximize accuracy and control over the output. Before using the prompt, replace the bracketed placeholders with your specific requirements.
**Prompt Structure:**
“`
Transcribe the following audio recording: [Audio File Path/URL or Input Method].
Transcription Parameters:
* **Audio Source:** [Specify the audio source – e.g., microphone, uploaded file, URL]
* **Output Format:** [Desired output format – e.g., plain text, JSON, SRT, WebVTT]
* **Language:** [Specify language of the audio – e.g., en-US, es-MX, fr-FR]
* **Diarization (Optional):** [If needed, request speaker diarization – e.g., “Please identify and label each speaker.”]
* **Profanity Filtering (Optional):** [Specify profanity filtering level – e.g., “Filter all profanity”, “Mark profanity with asterisks”]
* **Technical Terminology Handling (Optional):** [Provide specific technical terms expected in the audio – e.g., “The audio contains medical terminology related to cardiology.”]
* **Domain Specific Knowledge (Optional):** [Indicate the domain for context – e.g., “The audio is a legal deposition”, “The audio is a conversation about software development.”]
* **Punctuation and Capitalization:** [Specify punctuation and capitalization preferences – e.g., “Use proper punctuation and capitalization”, “No punctuation needed”]
* **Number Formatting (Optional):** [Specify how numbers should be transcribed – e.g., “Transcribe numbers as numerals”, “Transcribe numbers as words”]
* **Timestamping (Optional):** [Specify timestamp requirements – e.g., “Include timestamps every 5 seconds”, “Include timestamps for each speaker turn”]
* **Emphasis and Tone Detection (Optional):** [Request detection of emphasis or tone – e.g., “Detect and mark emphasized words”, “Analyze the speaker’s tone”]
* **Custom Instructions (Optional):** [Add any additional specific instructions – e.g., “Ignore background noise if possible”, “Transcribe only the sections between [start time] and [end time]”]
Error Handling Instructions:
* **Handling Uncertainties:** [Specify how to handle unclear audio – e.g., “Mark uncertain words with brackets []”, “Provide alternative transcriptions if possible”]
* **Handling Background Noise:** [Instructions for handling background noise – e.g., “Attempt to filter out background noise”, “Indicate sections with significant background noise”]
Output Example (Illustrative – Adjust based on your chosen parameters):
“`json
{
“transcript”: “This is an example transcription. [unclear word] It demonstrates the output structure.”,
“speakers”: [
{“start_time”: 0.0, “end_time”: 5.0, “speaker_label”: “Speaker 1”},
{“start_time”: 5.0, “end_time”: 10.0, “speaker_label”: “Speaker 2”}
],
“timestamps”: [
{“time”: 0.0, “text”: “This”},
{“time”: 0.5, “text”: “is”}
// … more timestamps
]
}
“`
“`
**Explanation and Best Practices:**
* **Dynamic Variables:** The bracketed placeholders allow you to tailor the prompt for each specific transcription task. This adaptability is crucial for optimizing results across different audio types and desired output formats.
* **Detailed Parameters:** Clearly defining parameters such as language, output format, and error handling instructions helps the AI model understand your expectations and produce more accurate results.
* **Optional Parameters:** The prompt includes optional parameters to address specific needs like speaker diarization, profanity filtering, and technical terminology handling. Only include the options relevant to your task.
* **Error Handling:** Providing specific instructions for handling uncertainties and background noise improves the reliability and usability of the transcription.
* **Output Example:** Including an illustrative output example helps guide the AI model towards the desired format and structure.
* **Platform Agnostic Design:** The prompt’s structure and clarity are designed to be effective across various AI platforms, ensuring consistent performance.
* **Iterative Refinement:** After receiving the transcription, review it and refine the prompt if necessary. For example, if specific terms were consistently mis-transcribed, add them to the “Technical Terminology Handling” section.
By using this dynamic prompt and adhering to the best practices outlined, you can significantly improve the accuracy and efficiency of your voice-to-text transcriptions across a wide range of AI platforms. Remember to always test and refine your prompts for optimal performance.