BranchesTags

Repository files navigation

Description

Voice assistant made with python 3 for Windows. It uses OpenAI's Whisper to convert speech to text. Speech Recognition is offline but online commands can be added. It understands English only.

You can get the latest build from the releases section.

Development Environment Setup

  1. Install Latest Version of Python 3 (Preferably 3.9.9 but should work on 3.8-3.10) and add to path
  2. Open terminal in the project directory.
  • If you have a GPU that supports CUDA toolkit then the performance can be increased.
  • Remove the # from the last line in the requirements.txt file.
  • NOTE: This will increase the download size by approx 2.0 GB.
  1. Create a virtual environment (Optional but Recommended)
    1. Type python -m venv env.
    2. Type .\env\Scripts\Activate.ps1
    • Note : On Windows, it may be required to enable the Activate.ps1 script by setting the execution policy for the user. You can do this by issuing the following command: Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser
  2. Type pip install -r requirements.txt
  3. "assistant.py" is the main file.
  • The program will download the "base.en" whisper model on the first launch (Approx. 140 MB).

Build

  1. Install pyinstaller
  2. Open terminal in the project directory.
  3. Type pyinstaller .\Sentinel.spec
  4. Application is built in the dist folder.

Commands

Open urls

  1. Open youtube
  2. Open stack
  3. Open udemy
  4. Open gmail
  5. Open whatsapp

Launch apps

  1. Open chrome (You may need to edit path in recognizer.py)
  2. Open code (You may need to edit path in recognizer.py)
  3. Open anaconda (You may need to edit path in recognizer.py)

Search

  1. Youtube "anything you want" (opens in default browser)
  2. Google "anything you want" (opens in default browser)

Shortcut to start listening for command-

"l_ctrl + l_alt + l_shift" (starts listening for the voice command) "l_ctrl + l_alt + q" (Closes the app) "l_ctrl + l_alt + c" (Calibrate the microphone) "l_ctrl + l_alt + s" (Toggle the window)

About

Voice Assistant using Whisper in python3

Topics

offline-speech-recognitionpythonspeech-recognitionttsvoice-assistant

Resources

Readme
Activity

Stars

4 stars

Watchers

1 watching

Forks

2 forks
Report repository

Releases

Used by

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
BranchesTags
Repository files navigation
Description
Voice assistant made with python 3 for Windows.
It uses OpenAI's Whisper to convert speech to text.
Speech Recognition is offline but online commands can be added.
It understands English only.
You can get the latest build from the releases section.
Development Environment Setup
  1. Install Latest Version of Python 3 (Preferably 3.9.9 but should work on 3.8-3.10) and add to path
  2. Open terminal in the project directory.
  • If you have a GPU that supports CUDA toolkit then the performance can be increased.
  • Remove the # from the last line in the requirements.txt file.
  • NOTE: This will increase the download size by approx 2.0 GB.
  1. Create a virtual environment (Optional but Recommended)

    1. Type python -m venv env.
    2. Type .\env\Scripts\Activate.ps1
    • Note : On Windows, it may be required to enable the Activate.ps1 script by setting the execution policy for the user. You can do this by issuing the following command: Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser
  2. Type pip install -r requirements.txt
  3. "assistant.py" is the main file.
  • The program will download the "base.en" whisper model on the first launch (Approx. 140 MB).
Build
  1. Install pyinstaller
  2. Open terminal in the project directory.
  3. Type pyinstaller .\Sentinel.spec
  4. Application is built in the dist folder.
Commands
Open urls
  1. Open youtube
  2. Open stack
  3. Open udemy
  4. Open gmail
  5. Open whatsapp
Launch apps
  1. Open chrome (You may need to edit path in recognizer.py)
  2. Open code (You may need to edit path in recognizer.py)
  3. Open anaconda (You may need to edit path in recognizer.py)
Search
  1. Youtube "anything you want" (opens in default browser)
  2. Google "anything you want" (opens in default browser)
Shortcut to start listening for command-
"l_ctrl + l_alt + l_shift" (starts listening for the voice command)
"l_ctrl + l_alt + q" (Closes the app)
"l_ctrl + l_alt + c" (Calibrate the microphone)
"l_ctrl + l_alt + s" (Toggle the window)
About
Voice Assistant using Whisper in python3
Topics
offline-speech-recognitionpythonspeech-recognitionttsvoice-assistant
Resources
Readme
Activity
Stars
4 stars
Watchers
1 watching
Forks
2 forks
Report repository
Releases
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Description
Voice assistant made with python 3 for Windows.
It uses OpenAI's Whisper to convert speech to text.
Speech Recognition is offline but online commands can be added.
It understands English only.
You can get the latest build from the releases section.
Development Environment Setup
  1. Install Latest Version of Python 3 (Preferably 3.9.9 but should work on 3.8-3.10) and add to path
  2. Open terminal in the project directory.
  • If you have a GPU that supports CUDA toolkit then the performance can be increased.
  • Remove the # from the last line in the requirements.txt file.
  • NOTE: This will increase the download size by approx 2.0 GB.
  1. Create a virtual environment (Optional but Recommended)

    1. Type python -m venv env.
    2. Type .\env\Scripts\Activate.ps1
    • Note : On Windows, it may be required to enable the Activate.ps1 script by setting the execution policy for the user. You can do this by issuing the following command: Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser
  2. Type pip install -r requirements.txt
  3. "assistant.py" is the main file.
  • The program will download the "base.en" whisper model on the first launch (Approx. 140 MB).
Build
  1. Install pyinstaller
  2. Open terminal in the project directory.
  3. Type pyinstaller .\Sentinel.spec
  4. Application is built in the dist folder.
Commands
Open urls
  1. Open youtube
  2. Open stack
  3. Open udemy
  4. Open gmail
  5. Open whatsapp
Launch apps
  1. Open chrome (You may need to edit path in recognizer.py)
  2. Open code (You may need to edit path in recognizer.py)
  3. Open anaconda (You may need to edit path in recognizer.py)
Search
  1. Youtube "anything you want" (opens in default browser)
  2. Google "anything you want" (opens in default browser)
Shortcut to start listening for command-
"l_ctrl + l_alt + l_shift" (starts listening for the voice command)
"l_ctrl + l_alt + q" (Closes the app)
"l_ctrl + l_alt + c" (Calibrate the microphone)
"l_ctrl + l_alt + s" (Toggle the window)
About
Voice Assistant using Whisper in python3
Topics
offline-speech-recognitionpythonspeech-recognitionttsvoice-assistant
Resources
Readme
Activity
Stars
4 stars
Watchers
1 watching
Forks
2 forks
Report repository
Releases
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Description
Voice assistant made with python 3 for Windows.
It uses OpenAI's Whisper to convert speech to text.
Speech Recognition is offline but online commands can be added.
It understands English only.
You can get the latest build from the releases section.
Development Environment Setup
  1. Install Latest Version of Python 3 (Preferably 3.9.9 but should work on 3.8-3.10) and add to path
  2. Open terminal in the project directory.
  • If you have a GPU that supports CUDA toolkit then the performance can be increased.
  • Remove the # from the last line in the requirements.txt file.
  • NOTE: This will increase the download size by approx 2.0 GB.
  1. Create a virtual environment (Optional but Recommended)

    1. Type python -m venv env.
    2. Type .\env\Scripts\Activate.ps1
    • Note : On Windows, it may be required to enable the Activate.ps1 script by setting the execution policy for the user. You can do this by issuing the following command: Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser
  2. Type pip install -r requirements.txt
  3. "assistant.py" is the main file.
  • The program will download the "base.en" whisper model on the first launch (Approx. 140 MB).
Build
  1. Install pyinstaller
  2. Open terminal in the project directory.
  3. Type pyinstaller .\Sentinel.spec
  4. Application is built in the dist folder.
Commands
Open urls
  1. Open youtube
  2. Open stack
  3. Open udemy
  4. Open gmail
  5. Open whatsapp
Launch apps
  1. Open chrome (You may need to edit path in recognizer.py)
  2. Open code (You may need to edit path in recognizer.py)
  3. Open anaconda (You may need to edit path in recognizer.py)
Search
  1. Youtube "anything you want" (opens in default browser)
  2. Google "anything you want" (opens in default browser)
Shortcut to start listening for command-
"l_ctrl + l_alt + l_shift" (starts listening for the voice command)
"l_ctrl + l_alt + q" (Closes the app)
"l_ctrl + l_alt + c" (Calibrate the microphone)
"l_ctrl + l_alt + s" (Toggle the window)
About
Voice Assistant using Whisper in python3
Topics
offline-speech-recognitionpythonspeech-recognitionttsvoice-assistant
Resources
Readme
Activity
Stars
4 stars
Watchers
1 watching
Forks
2 forks
Report repository
Releases
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
BranchesTags
Repository files navigation
Description
Voice assistant made with python 3 for Windows.
It uses OpenAI's Whisper to convert speech to text.
Speech Recognition is offline but online commands can be added.
It understands English only.
You can get the latest build from the releases section.
Development Environment Setup
  1. Install Latest Version of Python 3 (Preferably 3.9.9 but should work on 3.8-3.10) and add to path
  2. Open terminal in the project directory.
  • If you have a GPU that supports CUDA toolkit then the performance can be increased.
  • Remove the # from the last line in the requirements.txt file.
  • NOTE: This will increase the download size by approx 2.0 GB.
  1. Create a virtual environment (Optional but Recommended)

    1. Type python -m venv env.
    2. Type .\env\Scripts\Activate.ps1
    • Note : On Windows, it may be required to enable the Activate.ps1 script by setting the execution policy for the user. You can do this by issuing the following command: Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser
  2. Type pip install -r requirements.txt
  3. "assistant.py" is the main file.
  • The program will download the "base.en" whisper model on the first launch (Approx. 140 MB).
Build
  1. Install pyinstaller
  2. Open terminal in the project directory.
  3. Type pyinstaller .\Sentinel.spec
  4. Application is built in the dist folder.
Commands
Open urls
  1. Open youtube
  2. Open stack
  3. Open udemy
  4. Open gmail
  5. Open whatsapp
Launch apps
  1. Open chrome (You may need to edit path in recognizer.py)
  2. Open code (You may need to edit path in recognizer.py)
  3. Open anaconda (You may need to edit path in recognizer.py)
Search
  1. Youtube "anything you want" (opens in default browser)
  2. Google "anything you want" (opens in default browser)
Shortcut to start listening for command-
"l_ctrl + l_alt + l_shift" (starts listening for the voice command)
"l_ctrl + l_alt + q" (Closes the app)
"l_ctrl + l_alt + c" (Calibrate the microphone)
"l_ctrl + l_alt + s" (Toggle the window)
About
Voice Assistant using Whisper in python3
Topics
offline-speech-recognitionpythonspeech-recognitionttsvoice-assistant
Resources
Readme
Activity
Stars
4 stars
Watchers
1 watching
Forks
2 forks
Report repository
Releases
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Description
Voice assistant made with python 3 for Windows.
It uses OpenAI's Whisper to convert speech to text.
Speech Recognition is offline but online commands can be added.
It understands English only.
You can get the latest build from the releases section.
Development Environment Setup
  1. Install Latest Version of Python 3 (Preferably 3.9.9 but should work on 3.8-3.10) and add to path
  2. Open terminal in the project directory.
  • If you have a GPU that supports CUDA toolkit then the performance can be increased.
  • Remove the # from the last line in the requirements.txt file.
  • NOTE: This will increase the download size by approx 2.0 GB.
  1. Create a virtual environment (Optional but Recommended)

    1. Type python -m venv env.
    2. Type .\env\Scripts\Activate.ps1
    • Note : On Windows, it may be required to enable the Activate.ps1 script by setting the execution policy for the user. You can do this by issuing the following command: Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser
  2. Type pip install -r requirements.txt
  3. "assistant.py" is the main file.
  • The program will download the "base.en" whisper model on the first launch (Approx. 140 MB).
Build
  1. Install pyinstaller
  2. Open terminal in the project directory.
  3. Type pyinstaller .\Sentinel.spec
  4. Application is built in the dist folder.
Commands
Open urls
  1. Open youtube
  2. Open stack
  3. Open udemy
  4. Open gmail
  5. Open whatsapp
Launch apps
  1. Open chrome (You may need to edit path in recognizer.py)
  2. Open code (You may need to edit path in recognizer.py)
  3. Open anaconda (You may need to edit path in recognizer.py)
Search
  1. Youtube "anything you want" (opens in default browser)
  2. Google "anything you want" (opens in default browser)
Shortcut to start listening for command-
"l_ctrl + l_alt + l_shift" (starts listening for the voice command)
"l_ctrl + l_alt + q" (Closes the app)
"l_ctrl + l_alt + c" (Calibrate the microphone)
"l_ctrl + l_alt + s" (Toggle the window)
About
Voice Assistant using Whisper in python3
Topics
offline-speech-recognitionpythonspeech-recognitionttsvoice-assistant
Resources
Readme
Activity
Stars
4 stars
Watchers
1 watching
Forks
2 forks
Report repository
Releases
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Description
Voice assistant made with python 3 for Windows.
It uses OpenAI's Whisper to convert speech to text.
Speech Recognition is offline but online commands can be added.
It understands English only.
You can get the latest build from the releases section.
Development Environment Setup
  1. Install Latest Version of Python 3 (Preferably 3.9.9 but should work on 3.8-3.10) and add to path
  2. Open terminal in the project directory.
  • If you have a GPU that supports CUDA toolkit then the performance can be increased.
  • Remove the # from the last line in the requirements.txt file.
  • NOTE: This will increase the download size by approx 2.0 GB.
  1. Create a virtual environment (Optional but Recommended)

    1. Type python -m venv env.
    2. Type .\env\Scripts\Activate.ps1
    • Note : On Windows, it may be required to enable the Activate.ps1 script by setting the execution policy for the user. You can do this by issuing the following command: Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser
  2. Type pip install -r requirements.txt
  3. "assistant.py" is the main file.
  • The program will download the "base.en" whisper model on the first launch (Approx. 140 MB).
Build
  1. Install pyinstaller
  2. Open terminal in the project directory.
  3. Type pyinstaller .\Sentinel.spec
  4. Application is built in the dist folder.
Commands
Open urls
  1. Open youtube
  2. Open stack
  3. Open udemy
  4. Open gmail
  5. Open whatsapp
Launch apps
  1. Open chrome (You may need to edit path in recognizer.py)
  2. Open code (You may need to edit path in recognizer.py)
  3. Open anaconda (You may need to edit path in recognizer.py)
Search
  1. Youtube "anything you want" (opens in default browser)
  2. Google "anything you want" (opens in default browser)
Shortcut to start listening for command-
"l_ctrl + l_alt + l_shift" (starts listening for the voice command)
"l_ctrl + l_alt + q" (Closes the app)
"l_ctrl + l_alt + c" (Calibrate the microphone)
"l_ctrl + l_alt + s" (Toggle the window)
About
Voice Assistant using Whisper in python3
Topics
offline-speech-recognitionpythonspeech-recognitionttsvoice-assistant
Resources
Readme
Activity
Stars
4 stars
Watchers
1 watching
Forks
2 forks
Report repository
Releases
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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Description
Voice assistant made with python 3 for Windows.
It uses OpenAI's Whisper to convert speech to text.
Speech Recognition is offline but online commands can be added.
It understands English only.
You can get the latest build from the releases section.
Development Environment Setup
  1. Install Latest Version of Python 3 (Preferably 3.9.9 but should work on 3.8-3.10) and add to path
  2. Open terminal in the project directory.
  • If you have a GPU that supports CUDA toolkit then the performance can be increased.
  • Remove the # from the last line in the requirements.txt file.
  • NOTE: This will increase the download size by approx 2.0 GB.
  1. Create a virtual environment (Optional but Recommended)

    1. Type python -m venv env.
    2. Type .\env\Scripts\Activate.ps1
    • Note : On Windows, it may be required to enable the Activate.ps1 script by setting the execution policy for the user. You can do this by issuing the following command: Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser
  2. Type pip install -r requirements.txt
  3. "assistant.py" is the main file.
  • The program will download the "base.en" whisper model on the first launch (Approx. 140 MB).
Build
  1. Install pyinstaller
  2. Open terminal in the project directory.
  3. Type pyinstaller .\Sentinel.spec
  4. Application is built in the dist folder.
Commands
Open urls
  1. Open youtube
  2. Open stack
  3. Open udemy
  4. Open gmail
  5. Open whatsapp
Launch apps
  1. Open chrome (You may need to edit path in recognizer.py)
  2. Open code (You may need to edit path in recognizer.py)
  3. Open anaconda (You may need to edit path in recognizer.py)
Search
  1. Youtube "anything you want" (opens in default browser)
  2. Google "anything you want" (opens in default browser)
Shortcut to start listening for command-
"l_ctrl + l_alt + l_shift" (starts listening for the voice command)
"l_ctrl + l_alt + q" (Closes the app)
"l_ctrl + l_alt + c" (Calibrate the microphone)
"l_ctrl + l_alt + s" (Toggle the window)
About
Voice Assistant using Whisper in python3
Topics
offline-speech-recognitionpythonspeech-recognitionttsvoice-assistant
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1 watching
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