About Prompt
- Prompt Type – Dynamic
- Prompt Platform – ChatGPT, Grok, Deepseek, Gemini, Copilot, Midjourney, Meta AI and more
- Niche – Performance Analysis
- Language – English
- Category – Content Analysis
- Prompt Title – AI Prompt for Voice Emotion Analysis of Actors in Film Scenes
Prompt Details
This prompt is designed for dynamic voice emotion analysis of actors’ performances in film scenes for content analysis within the performance analysis niche. It is adaptable for various AI platforms and aims to provide detailed, specific guidance for generating insightful results.
**Prompt Structure:**
This prompt utilizes a structured approach, breaking down the request into key components to improve clarity and control. Replace the bracketed placeholders with specific information related to your analysis.
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**1. Data Input:**
* **Audio Source:** [Specify the audio source. E.g., “Provide the audio clip from [Film Title], [Scene Description – e.g., the argument scene between characters X and Y],” or “Upload the WAV file named [filename.wav]”]
* **Character Focus:** [Specify the character whose voice you want to analyze. E.g., “Focus on the performance of [Actor’s Name] as [Character’s Name].”]
* **Time Range (Optional):** [Specify the specific time range within the audio clip if needed. E.g., “Analyze the audio from [Start Time] to [End Time].”]
**2. Analysis Task:**
Analyze the provided audio clip to determine the emotional profile of the specified character’s vocal performance. Consider the following aspects:
* **Primary Emotions:** Identify the dominant emotions conveyed by the actor’s voice. Use a standardized emotion lexicon like Plutchik’s Wheel of Emotions (joy, sadness, anger, fear, trust, disgust, anticipation, surprise) or Ekman’s six basic emotions (anger, disgust, fear, happiness, sadness, surprise), or specify a custom lexicon if needed. Provide the identified emotions with confidence scores (e.g., “Anger: 85%, Fear: 15%”).
* **Emotional Nuances:** Beyond primary emotions, explore subtle emotional variations and complexities. Describe any shifts or transitions in emotion throughout the clip. For example, identify transitions from controlled anger to explosive rage, or subtle hints of sadness underlying a seemingly happy tone.
* **Vocal Qualities:** Analyze the acoustic characteristics of the voice that contribute to the emotional portrayal. Consider factors such as:
* **Pitch:** (High, low, varying)
* **Pace:** (Fast, slow, changes in tempo)
* **Volume:** (Loud, soft, dynamic range)
* **Tone:** (Harsh, gentle, resonant, breathy)
* **Pauses and Silence:** (Duration, frequency, placement)
* **Contextual Interpretation:** Relate the identified emotions and vocal qualities to the scene’s context. How does the actor’s vocal performance contribute to the narrative and character development? [Provide specific questions related to the scene’s context. E.g., “How does the character’s vocal performance reflect their power dynamic with the other character in the scene?” or “How does the actor use their voice to convey the character’s internal conflict?”]
**3. Output Format:**
Provide the analysis in a structured format, clearly separating the different aspects of the analysis. Use a format like JSON or a well-organized table to present the results. Example JSON structure:
“`json
{
“character”: “[Character Name]”,
“time_range”: “[Start Time] – [End Time]”,
“primary_emotions”: {
“anger”: 0.85,
“fear”: 0.15
},
“emotional_nuances”: “Transition from controlled anger to explosive rage noticeable at [Time Stamp]”,
“vocal_qualities”: {
“pitch”: “Varying, with higher pitch during moments of anger”,
“pace”: “Accelerates as anger intensifies”,
“volume”: “Increases significantly during outbursts”
},
“contextual_interpretation”: “The character’s vocal performance effectively conveys their struggle for control and the eventual eruption of their suppressed anger.”
}
“`
**4. Optional Parameters:**
* **Emotion Lexicon:** [Specify a specific emotion lexicon to be used, if different from the suggested ones.]
* **Focus on Specific Vocal Qualities:** [If you want to focus on specific vocal qualities, list them here. E.g., “Focus specifically on changes in pitch and pace.”]
* **Comparison Analysis:** [If you want to compare the performance in this clip to another clip, provide the details of the second clip. E.g., “Compare this performance to the actor’s performance in [Scene Description].”]
**Example Prompt Instance:**
“**Data Input:** Audio Source: Upload the WAV file named ‘scene_3_argument.wav’. Character Focus: Focus on the performance of Marlon Brando as Don Vito Corleone. Time Range: 00:02:00 to 00:03:00. **Analysis Task:** Analyze the provided audio clip […] **Contextual Interpretation:** How does Corleone’s vocal performance convey his authority and power within the scene? **Output Format:** Provide the analysis in JSON format.”
This dynamic prompt allows for detailed and specific control over the emotion analysis process, facilitating nuanced and contextually rich insights into actors’ vocal performances. Remember to adapt the bracketed placeholders with specific information related to your analysis.
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