About Prompt
- Prompt Type – Dynamic
- Prompt Platform – ChatGPT, Grok, Deepseek, Gemini, Copilot, Midjourney, Meta AI and more
- Niche – Video Editing
- Language – English
- Category – Video Processing
- Prompt Title – AI Prompt for Removing Background Noise from Video Clips
Prompt Details
This prompt is designed to be adaptable across various AI platforms for video processing and background noise removal. It aims to provide maximum control and specificity while maintaining dynamic functionality.
**Core Prompt Structure:**
“`
Remove background noise from the provided video clip [VIDEO_INPUT].
Focus on preserving the clarity and quality of the primary audio source(s), identified as [AUDIO_SOURCE_DESCRIPTION].
Consider these specific noise characteristics for removal: [NOISE_CHARACTERISTICS].
Apply the following processing parameters: [PROCESSING_PARAMETERS].
Output the processed video clip as [OUTPUT_FORMAT] with the filename [OUTPUT_FILENAME].
Provide a log or report detailing the noise reduction process, including:
* Identified noise profile
* Applied noise reduction techniques
* Any potential artifacts introduced
* Overall noise reduction level achieved (e.g., in dB)
“`
**Dynamic Prompt Elements and Examples:**
* **[VIDEO_INPUT]:** Provide the path or direct upload of the video clip.
* Example: `/path/to/video.mp4` or `upload://video.mov` (adapt for platform specifics). For platforms supporting direct input, this could be binary video data.
* **[AUDIO_SOURCE_DESCRIPTION]:** Describe the primary audio source to be preserved. This helps the AI differentiate between desired audio and noise. Be as specific as possible.
* Examples: “human speech,” “music from a guitar,” “narration from 00:05:00 to 00:06:30,” “audio from the center channel,” “audio emanating from the region bounded by [coordinates]” (if the platform supports spatial audio analysis).
* **[NOISE_CHARACTERISTICS]:** Detail the characteristics of the noise to be removed. The more specific, the better the results.
* Examples: “constant hum,” “wind noise,” “hissing sound,” “clicking sounds between 00:01:00 and 00:02:00,” “background chatter,” “intermittent buzzing,” “noise with a frequency range of [X Hz] to [Y Hz].”
* **[PROCESSING_PARAMETERS]:** Specify parameters to control the noise reduction process. Tailor these to the specific AI platform and desired outcome. Consider including:
* **Noise Reduction Strength/Level:** A numerical value or descriptive term (e.g., “low,” “medium,” “high,” “aggressive”).
* **Noise Reduction Algorithm/Method:** If the platform allows, specify a preferred algorithm (e.g., “spectral subtraction,” “Wiener filtering,” “deep learning-based noise reduction”).
* **Audio Compression:** Specify desired audio compression settings for the output (e.g., codec, bitrate).
* **Output Sample Rate:** Specify the desired output sample rate.
* **Advanced Parameters:** For platforms offering fine-grained control, provide parameters like noise floor, attack time, release time, and frequency smoothing bands.
* **[OUTPUT_FORMAT]:** Specify the desired output video format.
* Examples: `MP4`, `MOV`, `AVI`, `MKV`.
* **[OUTPUT_FILENAME]:** Provide the desired filename for the processed video.
* Example: `noise_reduced_video.mp4`
**Example Prompt 1 (Basic):**
“`
Remove background noise from the provided video clip upload://noisy_video.mp4.
Focus on preserving the clarity and quality of the primary audio source, identified as human speech.
Consider these specific noise characteristics for removal: constant hum and background chatter.
Output the processed video clip as MP4 with the filename cleaned_video.mp4.
“`
**Example Prompt 2 (Advanced):**
“`
Remove background noise from the provided video clip /path/to/conference_recording.mov.
Focus on preserving the clarity and quality of the primary audio source, identified as human speech from the presenter located in the region bounded by [x1, y1, x2, y2].
Consider these specific noise characteristics for removal: HVAC noise with a frequency range of 50 Hz to 150 Hz and intermittent keyboard clicks.
Apply the following processing parameters:
* Noise Reduction Algorithm: Deep learning-based noise reduction
* Noise Reduction Strength: Medium
* Output Sample Rate: 48kHz
* Audio Compression: AAC, 192kbps
Output the processed video clip as MOV with the filename processed_conference.mov.
Provide a detailed report of the noise reduction process.
“`
**Adapting the Prompt:**
This dynamic prompt structure provides a flexible template. Adapt the bracketed placeholders based on the specific capabilities and requirements of the target AI platform. Remember to consult the platform’s documentation for details on supported parameters and input/output formats. This adaptable approach ensures optimal noise reduction across a variety of AI tools.