AI Voice Designer
Run ID: 69cacba6eff1ba2b79624e172026-03-30Design
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Design a completely custom AI voice by describing the characteristics you want

AI Voice Designer: Panthera Prime - Professional Voice Profile

This document outlines the detailed design specifications for a custom AI voice, "Panthera Prime," tailored for professional, authoritative, and articulate communication. It includes comprehensive voice characteristics, conceptual interface descriptions, a complementary color palette, and key user experience (UX) recommendations.


1. Detailed Design Specifications: Panthera Prime Voice Profile

Voice Name: Panthera Prime

Core Purpose: To deliver information with clarity, authority, and approachability, suitable for high-stakes professional contexts.

Key Characteristics:

  • Gender Profile: Male
  • Age Profile: Mid-30s to Early 40s
  • Accent: Standard American English (Neutral, non-regional, highly intelligible)
  • Pitch: Mid-Low to Moderate range. Stable and resonant, conveying depth and gravitas without being overly deep or artificial.
  • Tone & Cadence:

* Clarity: Exceptional enunciation. Each word is distinct, ensuring maximum comprehension even in complex sentences.

* Pace: Moderate and controlled, approximately 140-160 words per minute. This allows for optimal information absorption without sounding rushed or overly slow. Natural, strategic pauses enhance emphasis and readability.

* Rhythm: Smooth and consistent, avoiding both robotic monotony and overly dramatic fluctuations. The rhythm is designed for sustained listening.

* Timbre: Rich, warm, and resonant. This vocal quality instills trust and professionalism, making the voice pleasant and engaging to listen to.

* Expressiveness: Professionally composed and articulate. Capable of conveying subtle nuances such as mild emphasis, analytical insight, and reassurance, but avoids overt emotionality. Inflections are natural, with a slight upward lift for questions and a firm downward close for definitive statements.

* Vocal Fry/Breathiness: Minimized to none, ensuring a clean, polished, and powerful sound.

  • Intended Use Cases:

* Executive summaries, corporate presentations, and quarterly reports.

* Professional narration for e-learning modules, documentaries, and explainer videos.

* High-level AI assistant for business intelligence, strategic planning, or critical system alerts.

* Official public announcements, corporate communications, and investor relations.

* Audiobooks in non-fiction, business, and academic genres.

  • Core Personality Attributes: Authoritative, Trustworthy, Articulate, Calm, Confident, Approachable, Intelligent.

2. Wireframe Descriptions: Voice Design Interface & Presentation

This section outlines the conceptual interface elements within an AI voice design tool (like ElevenLabs) that would facilitate the creation and refinement of "Panthera Prime," and how its output might be presented to an end-user.

2.1. Voice Design Interface (Conceptual)

This describes the controls and options a designer would interact with.

  • Core Parameter Sliders/Dials:

Gender Blend: Slider from "Masculine" to "Feminine" with a clear "Neutral" midpoint. (Setting for Panthera Prime: ~70-80% Masculine)*.

Age Range: Slider from "Young Adult" to "Senior," with distinct markers for "20s," "30s," "40s," "50s+." (Setting for Panthera Prime: Mid-30s to Early 40s)*.

Pitch Control: Fine-tune slider for "Lower" to "Higher" pitch, with an accompanying numerical value. (Setting for Panthera Prime: Slightly lower than midpoint)*.

Speech Rate: Slider for "Slow" (e.g., 100 WPM) to "Fast" (e.g., 200 WPM), with a baseline "Normal" (150 WPM) marked. (Setting for Panthera Prime: Moderate, ~1.0x baseline)*.

Intonation/Expressiveness: Slider from "Monotone" to "Highly Expressive." (Setting for Panthera Prime: "Professionally Expressive" – avoiding extremes)*.

Clarity/Enunciation: Slider from "Muffled" to "Crisp." (Setting for Panthera Prime: Maximized for clarity)*.

Timbre Richness: Slider from "Thin" to "Resonant." (Setting for Panthera Prime: High Resonant)*.

Accent Selector: Dropdown menu offering a curated list of major accents (e.g., "Standard American English," "British RP," "Australian," "Indian English," etc.). (Setting for Panthera Prime: Standard American English)*.

  • Voice Style Presets: A gallery of pre-defined base styles such as "Narrator," "Presenter," "AI Assistant (Formal)," "Friendly," "Energetic," "Calm." (Starting point for Panthera Prime: "Presenter" or "AI Assistant (Formal)").
  • Text Input Field: A large, multi-line text area for users to type or paste content for real-time voice preview.
  • Preview Button: An immediate "Play" button to generate and listen to the audio based on the current settings.
  • Save/Export Options: Clearly labeled buttons for "Save Voice Profile" (to the user's library) and "Export Audio" (with format options like MP3, WAV, FLAC).
  • Advanced Settings (Toggleable Section):

* Emphasis Control: Allows users to highlight specific words or phrases to be spoken with stronger emphasis.

* Pause Control: Enables insertion of custom pause durations (e.g., <break time="750ms"/> via SSML).

* SSML Support: Full integration and display of Speech Synthesis Markup Language for granular control over pronunciation, intonation, and timing.

2.2. Voice Presentation/Integration (Conceptual)

This describes how the "Panthera Prime" voice would be experienced by an end-user in an application.

  • Minimalist Audio Player Component: A clean, unobtrusive player featuring basic controls (play/pause, scrub bar, volume). The player should clearly indicate the voice being used (e.g., "Narrated by Panthera Prime AI").
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"+slugTitle(pn)+"

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Built with PantheraHive BOS

\n
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"+slugTitle(pn)+"

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Built with PantheraHive BOS

\n
\n \n
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zip.file(folder+".gitignore","node_modules/\ndist/\n.env\n.DS_Store\n*.local\n.angular/\n"); } /* --- Python --- */ function buildPython(zip,folder,app,code){ var title=slugTitle(app); var pn=pkgName(app); var src=code.replace(/^\`\`\`[\w]*\n?/m,"").replace(/\n?\`\`\`$/m,"").trim(); var reqMap={"numpy":"numpy","pandas":"pandas","sklearn":"scikit-learn","tensorflow":"tensorflow","torch":"torch","flask":"flask","fastapi":"fastapi","uvicorn":"uvicorn","requests":"requests","sqlalchemy":"sqlalchemy","pydantic":"pydantic","dotenv":"python-dotenv","PIL":"Pillow","cv2":"opencv-python","matplotlib":"matplotlib","seaborn":"seaborn","scipy":"scipy"}; var reqs=[]; Object.keys(reqMap).forEach(function(k){if(src.indexOf("import "+k)>=0||src.indexOf("from "+k)>=0)reqs.push(reqMap[k]);}); var reqsTxt=reqs.length?reqs.join("\n"):"# add dependencies here\n"; zip.file(folder+"main.py",src||"# "+title+"\n# Generated by PantheraHive BOS\n\nprint(title+\" loaded\")\n"); zip.file(folder+"requirements.txt",reqsTxt); zip.file(folder+".env.example","# Environment variables\n"); zip.file(folder+"README.md","# "+title+"\n\nGenerated by PantheraHive BOS.\n\n## Setup\n\`\`\`bash\npython3 -m venv .venv\nsource .venv/bin/activate\npip install -r requirements.txt\n\`\`\`\n\n## Run\n\`\`\`bash\npython main.py\n\`\`\`\n"); zip.file(folder+".gitignore",".venv/\n__pycache__/\n*.pyc\n.env\n.DS_Store\n"); } /* --- Node.js --- */ function buildNode(zip,folder,app,code){ var title=slugTitle(app); var pn=pkgName(app); var src=code.replace(/^\`\`\`[\w]*\n?/m,"").replace(/\n?\`\`\`$/m,"").trim(); var depMap={"mongoose":"^8.0.0","dotenv":"^16.4.5","axios":"^1.7.9","cors":"^2.8.5","bcryptjs":"^2.4.3","jsonwebtoken":"^9.0.2","socket.io":"^4.7.4","uuid":"^9.0.1","zod":"^3.22.4","express":"^4.18.2"}; var deps={}; Object.keys(depMap).forEach(function(k){if(src.indexOf(k)>=0)deps[k]=depMap[k];}); if(!deps["express"])deps["express"]="^4.18.2"; var pkgJson=JSON.stringify({"name":pn,"version":"1.0.0","main":"src/index.js","scripts":{"start":"node src/index.js","dev":"nodemon src/index.js"},"dependencies":deps,"devDependencies":{"nodemon":"^3.0.3"}},null,2)+"\n"; 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