{"id":1449,"date":"2024-12-28T13:46:22","date_gmt":"2024-12-28T13:46:22","guid":{"rendered":"https:\/\/ai-box.eu\/?p=1449"},"modified":"2025-01-31T19:39:03","modified_gmt":"2025-01-31T19:39:03","slug":"how-to-install-and-use-openais-whisper-locally-for-automatic-transcription-and-translation","status":"publish","type":"post","link":"https:\/\/ai-box.eu\/en\/news\/how-to-install-and-use-openais-whisper-locally-for-automatic-transcription-and-translation\/1449\/","title":{"rendered":"How to Install and Use OpenAI\u2019s Whisper Locally for Automatic Transcription and Translation"},"content":{"rendered":"<p>Imagine having an effortless way to convert your favorite podcasts, YouTube videos, or conference recordings into readable text\u2014or instantly translate them from one language to another without lifting a finger. Whether you\u2019re a content creator, researcher, or simply someone looking to save time, <strong>OpenAI\u2019s Whisper<\/strong> is a game-changer.<\/p>\n<p><strong>Whisper<\/strong> excels at <strong>automatic translation<\/strong> and <strong>transcription<\/strong> of audio files, thanks to its advanced neural architecture and extensive multilingual support. It can not only <strong>transcribe<\/strong> audio into text with impressive accuracy but also <strong>translate<\/strong> it into another language in one seamless step. From generating subtitles for your global audience to simplifying your post-production workflows, Whisper is built to deliver results right out of the box.<\/p>\n<p>Whisper is a general-purpose speech recognition model released by OpenAI. It can:<\/p>\n<ul>\n<li>Transcribe audio files in various languages.<\/li>\n<li>Translate them into English (or other languages depending on configuration).<\/li>\n<\/ul>\n<p>It offers a broad range of pre-trained model sizes (from tiny to large). The larger the model, the more accurate it tends to be but also the more computational resources it requires.<\/p>\n<p><iframe loading=\"lazy\" title=\"YouTube video player\" src=\"https:\/\/www.youtube-nocookie.com\/embed\/f0xf48qZ_uk?si=UNS4fHrxqG7a6JYV\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><br \/>\nIn this guide, we\u2019ll dive deep into setting up Whisper on Ubuntu using my custom installation script, then walk you through the process of transcribing and translating audio tracks. Whether you\u2019re working with local files or video URLs, this solution has you covered. The new interface now includes two processing tabs\u2014one for local files and another for video URLs\u2014making it even more versatile and user-friendly.<\/p>\n<p>The picture below shows my Gradio Web-App, which I\u2019ve written to use OpenAI&#8217;s Whisper models to transcribe and translate audio files.<\/p>\n<div id=\"attachment_1458\" style=\"width: 1034px\" class=\"wp-caption alignnone\"><a href=\"https:\/\/ai-box.eu\/wp-content\/uploads\/2024\/12\/Whisper_Transcribe_Translate_audio_video.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-1458\" class=\"wp-image-1458 size-large\" src=\"https:\/\/ai-box.eu\/wp-content\/uploads\/2024\/12\/Whisper_Transcribe_Translate_audio_video-1024x887.jpg\" alt=\"Whisper Transcribe &amp; Translate audio video\" width=\"1024\" height=\"887\" srcset=\"https:\/\/ai-box.eu\/wp-content\/uploads\/2024\/12\/Whisper_Transcribe_Translate_audio_video-1024x887.jpg 1024w, https:\/\/ai-box.eu\/wp-content\/uploads\/2024\/12\/Whisper_Transcribe_Translate_audio_video-300x260.jpg 300w, https:\/\/ai-box.eu\/wp-content\/uploads\/2024\/12\/Whisper_Transcribe_Translate_audio_video-768x665.jpg 768w, https:\/\/ai-box.eu\/wp-content\/uploads\/2024\/12\/Whisper_Transcribe_Translate_audio_video-1080x936.jpg 1080w, https:\/\/ai-box.eu\/wp-content\/uploads\/2024\/12\/Whisper_Transcribe_Translate_audio_video.jpg 1488w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/a><p id=\"caption-attachment-1458\" class=\"wp-caption-text\">Whisper Transcribe &amp; Translate audio video<\/p><\/div>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_2 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/ai-box.eu\/en\/news\/how-to-install-and-use-openais-whisper-locally-for-automatic-transcription-and-translation\/1449\/#1_Prerequisites\" >1. Prerequisites<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/ai-box.eu\/en\/news\/how-to-install-and-use-openais-whisper-locally-for-automatic-transcription-and-translation\/1449\/#Hardware_and_System_Requirements\" >Hardware and System Requirements<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/ai-box.eu\/en\/news\/how-to-install-and-use-openais-whisper-locally-for-automatic-transcription-and-translation\/1449\/#Additional_Dependencies\" >Additional Dependencies<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/ai-box.eu\/en\/news\/how-to-install-and-use-openais-whisper-locally-for-automatic-transcription-and-translation\/1449\/#2_Installation_Using_the_Script\" >2. Installation Using the Script<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/ai-box.eu\/en\/news\/how-to-install-and-use-openais-whisper-locally-for-automatic-transcription-and-translation\/1449\/#21_Cloning_the_Repository\" >2.1 Cloning the Repository<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/ai-box.eu\/en\/news\/how-to-install-and-use-openais-whisper-locally-for-automatic-transcription-and-translation\/1449\/#22_Running_the_Whisper_Installation_Script\" >2.2 Running the Whisper Installation Script<\/a><ul class='ez-toc-list-level-4' ><li class='ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/ai-box.eu\/en\/news\/how-to-install-and-use-openais-whisper-locally-for-automatic-transcription-and-translation\/1449\/#What_Does_the_Script_Do\" >What Does the Script Do?<\/a><\/li><\/ul><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/ai-box.eu\/en\/news\/how-to-install-and-use-openais-whisper-locally-for-automatic-transcription-and-translation\/1449\/#3_Using_Whisper_Two_Processing_Options\" >3. Using Whisper: Two Processing Options<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/ai-box.eu\/en\/news\/how-to-install-and-use-openais-whisper-locally-for-automatic-transcription-and-translation\/1449\/#31_Local_File_Processing\" >3.1 Local File Processing<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/ai-box.eu\/en\/news\/how-to-install-and-use-openais-whisper-locally-for-automatic-transcription-and-translation\/1449\/#32_Video_URL_Processing\" >3.2 Video URL Processing<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/ai-box.eu\/en\/news\/how-to-install-and-use-openais-whisper-locally-for-automatic-transcription-and-translation\/1449\/#33_Running_the_Sample_Python_Script\" >3.3 Running the Sample Python Script<\/a><ul class='ez-toc-list-level-4' ><li class='ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/ai-box.eu\/en\/news\/how-to-install-and-use-openais-whisper-locally-for-automatic-transcription-and-translation\/1449\/#Key_Points_in_This_Script\" >Key Points in This Script<\/a><\/li><\/ul><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/ai-box.eu\/en\/news\/how-to-install-and-use-openais-whisper-locally-for-automatic-transcription-and-translation\/1449\/#4_Verification_and_Troubleshooting\" >4. Verification and Troubleshooting<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/ai-box.eu\/en\/news\/how-to-install-and-use-openais-whisper-locally-for-automatic-transcription-and-translation\/1449\/#5_Autostart_of_the_Local_Whisper_Service\" >5. Autostart of the Local Whisper Service<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/ai-box.eu\/en\/news\/how-to-install-and-use-openais-whisper-locally-for-automatic-transcription-and-translation\/1449\/#6_Conclusion\" >6. Conclusion<\/a><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"1_Prerequisites\"><\/span>1. Prerequisites<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>I am running at home an Ubuntu server with a NVIDIA RTX A6000 and that&#8217;s why I always describe my setup for Ubuntu.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Hardware_and_System_Requirements\"><\/span>Hardware and System Requirements<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul>\n<li><strong>Ubuntu<\/strong> (Tested on Ubuntu 20.04 and above; other Linux distros may also work).<\/li>\n<li><strong>Python 3.7+<\/strong> installed.<\/li>\n<li><strong>Sufficient disk space<\/strong> to store the Whisper model files (the <code>large-v2<\/code> model is about 2GB).<\/li>\n<li>An NVIDIA GPU (optional but recommended) with CUDA support for faster inference. If you don\u2019t have a GPU, Whisper will still work on CPU, albeit more slowly.<\/li>\n<\/ul>\n<h3><span class=\"ez-toc-section\" id=\"Additional_Dependencies\"><\/span>Additional Dependencies<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul>\n<li><strong>FFmpeg<\/strong> for handling various audio\/video formats.<\/li>\n<li><strong>yt-dlp<\/strong> is a feature-rich command-line audio\/video downloader with support for thousands of sites.<\/li>\n<li><strong>Pip<\/strong> for installing Python packages.<\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"2_Installation_Using_the_Script\"><\/span>2. Installation Using the Script<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>I\u2019ve created a custom script to streamline Whisper installation on Ubuntu. The script is available in my <a href=\"https:\/\/github.com\/custom-build-robots\/Installation-Scripts-for-Generative-AI-Tools\/blob\/main\/install_whisper.sh\" target=\"_new\" rel=\"noopener\">GitHub repository for Installation Scripts for Generative AI Tools<\/a>.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"21_Cloning_the_Repository\"><\/span>2.1 Cloning the Repository<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Open your terminal and clone the repository:<\/p>\n<p style=\"padding-left: 40px;\"><code>git clone https:\/\/github.com\/custom-build-robots\/Installation-Scripts-for-Generative-AI-Tools.git<\/code><br \/>\n<code>cd Installation-Scripts-for-Generative-AI-Tools<\/code><\/p>\n<h3><span class=\"ez-toc-section\" id=\"22_Running_the_Whisper_Installation_Script\"><\/span>2.2 Running the Whisper Installation Script<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Inside the cloned repository, you\u2019ll find <code>install_whisper.sh<\/code>. Make sure it\u2019s executable, then run it:<\/p>\n<p style=\"padding-left: 40px;\"><code>chmod +x install_whisper.sh<\/code><br \/>\n<code>.\/install_whisper.sh<\/code><\/p>\n<h4><span class=\"ez-toc-section\" id=\"What_Does_the_Script_Do\"><\/span>What Does the Script Do?<span class=\"ez-toc-section-end\"><\/span><\/h4>\n<ol>\n<li><strong>Installs FFmpeg<\/strong> \u2013 This is crucial for audio\/video processing.<\/li>\n<li><strong>Installs Python dependencies<\/strong> \u2013 Ensures <code>pip<\/code>, <code>torch<\/code>, and <code>whisper<\/code> are available.<\/li>\n<li><strong>Creates a folder<\/strong> to house your Whisper models.<\/li>\n<\/ol>\n<p>Once the script completes, you should have a working Whisper environment on your Ubuntu system.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"3_Using_Whisper_Two_Processing_Options\"><\/span>3. Using Whisper: Two Processing Options<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<h3><span class=\"ez-toc-section\" id=\"31_Local_File_Processing\"><\/span>3.1 Local File Processing<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>You can upload audio or video files directly from your local machine. The Web-App will transcribe or translate the content based on your chosen settings. Supported formats include MP3, WAV, and MP4.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"32_Video_URL_Processing\"><\/span>3.2 Video URL Processing<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>With the video URL tab, you can paste a YouTube or other video link. The app will download the video, process the audio, and output a transcription or translation. This is made possible by integrating <code>yt-dlp<\/code> and FFmpeg.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"33_Running_the_Sample_Python_Script\"><\/span>3.3 Running the Sample Python Script<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Below is the script I use to run Whisper, specifying a custom download directory for the model. This example demonstrates how to <strong>translate<\/strong> Japanese audio into English text. You can also transcribe audio if you don\u2019t need language conversion.<\/p>\n<p style=\"padding-left: 40px;\"><strong>Download:<\/strong> <a href=\"https:\/\/github.com\/custom-build-robots\/OpenAI-whisper-transcribe-or-translate-locally\" target=\"_blank\" rel=\"noopener\">OpenAI-whisper-transcribe-or-translate-locally<\/a><\/p>\n<h4><span class=\"ez-toc-section\" id=\"Key_Points_in_This_Script\"><\/span>Key Points in This Script<span class=\"ez-toc-section-end\"><\/span><\/h4>\n<ol>\n<li><strong><code>model_path<\/code> and <code>model_name<\/code><\/strong>: You can choose which Whisper model you want to use (e.g., <code>base<\/code>, <code>small<\/code>, <code>medium<\/code>, <code>large-v2<\/code>). Larger models = better accuracy but higher memory usage.<\/li>\n<li><strong><code>language<\/code><\/strong>: Set this if you know the source language; it helps speed up processing and ensures better results when translating.<\/li>\n<li><strong><code>task<\/code><\/strong>: If set to <code>\"transcribe\"<\/code>, you get text in the original language. If set to <code>\"translate\"<\/code>, you get text translated into English (default).<\/li>\n<li><strong>Saved Transcriptions<\/strong>: The transcribed\/translated text is stored in a <code>.txt<\/code> file next to your audio file.<\/li>\n<\/ol>\n<h2><span class=\"ez-toc-section\" id=\"4_Verification_and_Troubleshooting\"><\/span>4. Verification and Troubleshooting<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<ul>\n<li><strong>Model Storage<\/strong>: Check that the model files (<code>.pt<\/code>) are actually in the <code>models\/<\/code> folder. If not, Whisper downloads them automatically.<\/li>\n<li><strong>GPU Support<\/strong>: By default, Whisper will attempt to use a GPU if PyTorch detects one. If you want to force CPU usage, set the environment variable <code>export CUDA_VISIBLE_DEVICES=\"\"<\/code> before running your script.<\/li>\n<li><strong>Performance<\/strong>: If you\u2019re transcribing\/translating large files or using big models, you might experience high memory usage. Consider smaller models (like <code>medium<\/code> or <code>small<\/code>) if resources are limited.<\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"5_Autostart_of_the_Local_Whisper_Service\"><\/span>5. Autostart of the Local Whisper Service<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Please create the following file as described below.<\/p>\n<p style=\"padding-left: 40px;\"><strong>Command:<\/strong> <code>sudo nano \/etc\/systemd\/system\/whisper.service<\/code><\/p>\n<p>Now insert the following lines. Ensure to adjust the path to where your Python program is located. Also, note that I am using a virtual environment named <code>venv_whisper<\/code> in which my local Whisper service is running.<\/p>\n<p style=\"padding-left: 40px;\"><code>[Unit]<\/code><br \/>\n<code>Description=Whisper Transcribe &amp; Translate Gradio App<\/code><br \/>\n<code>After=network.target<\/code><\/p>\n<p style=\"padding-left: 40px;\"><code>[Service]<\/code><br \/>\n<code>User=ingmar<\/code><br \/>\n<code>WorkingDirectory=\/home\/ingmar\/whisper_offline<\/code><br \/>\n<code>ExecStart=\/bin\/bash -c 'source \/home\/ingmar\/whisper_offline\/venv_whisper\/bin\/activate &amp;&amp; python3 <strong>\/home\/ingmar\/whisper_offline\/whisper_gradio_app.py<\/strong>'<\/code><br \/>\n<code>Restart=always<\/code><br \/>\n<code>Environment=PYTHONUNBUFFERED=1<\/code><br \/>\n<code>StandardOutput=journal<\/code><br \/>\n<code>StandardError=journal<\/code><\/p>\n<p style=\"padding-left: 40px;\"><code>[Install]<\/code><br \/>\n<code>WantedBy=multi-user.target<\/code><\/p>\n<p>Now save the <code>whisper.service<\/code> file after customizing it for your needs.<\/p>\n<p>Make the <code>whisper.service<\/code> file executable with the following command:<\/p>\n<p style=\"padding-left: 40px;\"><strong>Command:<\/strong> <code>sudo <span class=\"hljs-built_in\">chmod<\/span> 644 \/etc\/systemd\/system\/whisper.service<\/code><\/p>\n<p>Next, execute the following three commands to set up the service in the Ubuntu system:<\/p>\n<p style=\"padding-left: 40px;\"><strong>Command:<\/strong> <code>sudo systemctl daemon-reload<\/code><\/p>\n<p style=\"padding-left: 40px;\"><strong>Command:<\/strong> <code>sudo systemctl enable whisper.service<\/code><\/p>\n<p style=\"padding-left: 40px;\"><strong>Command:<\/strong> <code>sudo systemctl start whisper.service<\/code><\/p>\n<p>You can now check whether the service is running with the following command:<\/p>\n<p style=\"padding-left: 40px;\"><strong>Command:<\/strong> <code>sudo systemctl status whisper.service<\/code><\/p>\n<p>From now on, the local Whisper service should be online, and you can access it in your browser.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"6_Conclusion\"><\/span>6. Conclusion<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Whisper is a powerful tool for speech recognition and translation. By leveraging my installation script on Ubuntu, you can simplify the setup process. With the new two-tab Web-App interface, processing audio from local files or video URLs has never been easier. Explore Whisper\u2019s capabilities today and unlock a world of transcription and translation possibilities!<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Imagine having an effortless way to convert your favorite podcasts, YouTube videos, or conference recordings into readable text\u2014or instantly translate them from one language to another without lifting a finger. Whether you\u2019re a content creator, researcher, or simply someone looking to save time, OpenAI\u2019s Whisper is a game-changer. Whisper excels at automatic translation and transcription [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":1458,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[162,8,51,50],"tags":[],"class_list":["post-1449","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-large-language-models-en","category-news","category-software-en","category-top-story-en","et-has-post-format-content","et_post_format-et-post-format-standard"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>How to Install and Use OpenAI\u2019s Whisper Locally for Automatic Transcription and Translation - Exploring the Future: Inside the AI Box<\/title>\n<meta name=\"description\" content=\"Learn how to seamlessly install and configure OpenAI\u2019s Whisper on Ubuntu for automatic audio transcription and translation. 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