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Docs: Final polish - Enshittification manifesto and structural refinement

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## 📡 The Transmission ## 📡 The Transmission
We live in an era of enclosure. Our words, our thoughts, and our digital footprints are strip-mined by centralized giants, turned into capital, and sold back to us as "convenience." We are witnessing the **enshittification** of the digital world. What were once vibrant social commons are being walled off, strip-mined for data, and degraded into rent-seeking silos. Your voice is no longer your own; it is a training set for a corporate oracle that charges you for the privilege of listening.
**Whisper Voice** is a rejection of that contract. **Whisper Voice** is a small act of sabotage against this trend.
It is built on the axiom that **your voice belongs to you**. By bringing state-of-the-art inference down from the server farms and running it on your own metal, we reclaim a small piece of the digital commons. This software answers to no one but you. It has no telemetry, no subscription, and no masters. It is built on the axiom of **Technological Sovereignty**. By moving state-of-the-art inference from the server farms to your own silicon, you reclaim the means of digital production. No telemetry. No subscriptions. No "cloud processing" that eavesdrops on your intent.
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## ⚡ The Engine ## ⚡ The Engine
This operates on the silicon. It is not a wrapper. It is a machine. Whisper Voice operates directly on the metal. It is not an API wrapper; it is an autonomous machine.
| Component | Technology | Benefit | | Component | Technology | Benefit |
| :--- | :--- | :--- | | :--- | :--- | :--- |
| **Inference Core** | **Faster-Whisper** | Hyper-optimized implementation via **CTranslate2**. Delivers **4x velocity** over standard PyTorch execution. | | **Inference Core** | **Faster-Whisper** | Hyper-optimized C++ implementation via **CTranslate2**. Delivers **4x velocity** over standard PyTorch. |
| **Compression** | **INT8 quantization** | Enables Pro-grade models (`Large-v3`) to run on consumer hardware, democratizing access to high-fidelity AI. | | **Compression** | **INT8 quantization** | Enables Pro-grade models (`Large-v3`) to run on consumer-grade GPUs, democratizing elite AI. |
| **Sensory Gate** | **Silero VAD** | Enterprise-grade Voice Activity Detection filters out the noise, ensuring only intent is captured. | | **Sensory Gate** | **Silero VAD** | Enterprise-grade Voice Activity Detection filters out the noise, ensuring only pure intent is processed. |
| **Interface** | **Qt 6 / QML** | Hardware-accelerated, glassmorphic UI that is fluid, responsive, and sovereign. | | **Interface** | **Qt 6 / QML** | Hardware-accelerated, glassmorphic UI that is fluid, responsive, and sovereign. |
<br> <br>
## 🌎 Universal Translator ## 🖋️ Universal Transcription
Whisper Voice v1.0.1 introduces a **Neural Translation Engine** built directly into the core. It bypasses the need for corporate translation APIs entirely. At its core, Whisper Voice is the ultimate bridge between thought and text. It listens with superhuman precision, converting spoken word into written form across **99 languages**.
* **Punctuation Mastery**: Automatically handles capitalization and complex punctuation formatting.
* **Contextual Intelligence**: Smarter than standard dictation; it understands the flow of sentences to resolve homophones and technical jargon ($1.5k vs "fifteen hundred dollars").
* **Total Privacy**: Your private dictation, legal notes, or creative writing never leave your RAM.
### Workflow: `F9 (Default)`
The primary channel for native-language transcription. It transcribes precisely what it hears in the language you speak (or the one you've locked in Settings).
<br>
## 🌎 Universal Translation
Whisper Voice v1.0.1 includes a **Neural Translation Engine** that allows you to bridge any linguistic gap instantly.
* **Input**: Speak in French, Japanese, Russian, or **96 other languages**. * **Input**: Speak in French, Japanese, Russian, or **96 other languages**.
* **Output**: The engine instantly reconstructs the semantic meaning in fluent **English**. * **Output**: The engine instantly reconstructs the semantic meaning into fluent **English**.
* **Local Execution**: No API keys. No data leaks. The translation happens on your GPU. * **Task Protocol**: Handled via the dedicated `F10` channel.
### Dual-Channel Workflow ### 🔍 Why only English translation?
The application listens on two separate channels simultaneously, allowing for seamless fluid switching between local and international communication. A common question arises: *Why can't I translate from French to Japanese?*
* **F9 (Default)** -> **Transcribe**: Types exactly what you say, in the language you speak. The architecture of the underlying Whisper model is a **Many-to-English** design. During its massive training phase (680,000 hours of audio), the translation task was specifically optimized to map the global linguistic commons onto a single bridge language: **English**. This allowed the model to reach incredible levels of semantic understanding without the exponential complexity of a "Many-to-Many" mapping.
* **F10 (Default)** -> **Translate**: Translates whatever you say in *any* language into English.
By focusing its translation decoder solely on English, Whisper achieves "Zero-Shot" quality that rivals specialized translation engines while remaining lightweight enough to run on your local GPU.
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## <EFBFBD> Supported Languages ## 🌐 Supported Languages
The engine understands the following 99 languages. You can lock the focus to a specific language in Settings to improve accuracy, or rely on **Auto-Detect** for fluid multilingual usage. The engine understands the following 99 languages. You can lock the focus to a specific language in Settings to improve accuracy, or rely on **Auto-Detect** for fluid multilingual usage.
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| Faroese 🇫🇴 | Finnish 🇫🇮 | Flemish 🇧🇪 | French 🇫🇷 | Galician 🇪🇸 | Georgian 🇬🇪 | | Faroese 🇫🇴 | Finnish 🇫🇮 | Flemish 🇧🇪 | French 🇫🇷 | Galician 🇪🇸 | Georgian 🇬🇪 |
| German 🇩🇪 | Greek 🇬🇷 | Gujarati 🇮🇳 | Haitian 🇭🇹 | Hausa 🇳🇬 | Hawaiian 🇺🇸 | | German 🇩🇪 | Greek 🇬🇷 | Gujarati 🇮🇳 | Haitian 🇭🇹 | Hausa 🇳🇬 | Hawaiian 🇺🇸 |
| Hebrew 🇮🇱 | Hindi 🇮🇳 | Hungarian 🇭🇺 | Icelandic 🇮🇸 | Indonesian 🇮🇩 | Italian 🇮🇹 | | Hebrew 🇮🇱 | Hindi 🇮🇳 | Hungarian 🇭🇺 | Icelandic 🇮🇸 | Indonesian 🇮🇩 | Italian 🇮🇹 |
| Japanese 🇯🇵 | Javanese 🇮🇩 | Kannada 🇮🇳 | Kazakh 🇰🇿 | Khmer 🇰🇭 | Korean 🇰🇷 | | Japanese 🇯🇵 | Javanese 🇮 Indonesa | Kannada 🇮🇳 | Kazakh 🇰🇿 | Khmer 🇰🇭 | Korean 🇰🇷 |
| Lao 🇱🇦 | Latin 🇻🇦 | Latvian 🇱🇻 | Lingala 🇨🇩 | Lithuanian 🇱🇹 | Luxembourgish 🇱🇺 | | Lao 🇱🇦 | Latin 🇻🇦 | Latvian 🇱🇻 | Lingala 🇨🇩 | Lithuanian 🇱🇹 | Luxembourgish 🇱🇺 |
| Macedonian 🇲🇰 | Malagasy 🇲🇬 | Malay 🇲🇾 | Malayalam 🇮🇳 | Maltese 🇲🇹 | Maori 🇳🇿 | | Macedonian 🇲🇰 | Malagasy 🇲🇬 | Malay 🇲🇾 | Malayalam 🇮🇳 | Maltese 🇲🇹 | Maori 🇳🇿 |
| Marathi 🇮🇳 | Moldavian 🇲🇩 | Mongolian 🇲🇳 | Myanmar 🇲🇲 | Nepali 🇳🇵 | Norwegian 🇳🇴 | | Marathi 🇮🇳 | Moldavian 🇲🇩 | Mongolian 🇲🇳 | Myanmar 🇲🇲 | Nepali 🇳🇵 | Norwegian 🇳🇴 |