How to transcribe audio to text? Audio to text converter | Free | Python 2023
TLDRThis tutorial video demonstrates how to install a free Python audio-to-text transcriber called 'whisper' by Open AI on a Windows computer. The process involves installing Anaconda, setting up a Python environment, and downloading the necessary application files. It guides through activating the environment, installing additional required packages, and using the medium model for transcription. The video also shows how to navigate to the audio file location, execute the transcription command, and obtain the transcribed text. It concludes with instructions on how to run the transcription process again and offers help commands for further exploration.
Takeaways
- 😀 Install Python using Anaconda for the audio to text transcribing application.
- 🔍 Use the Anaconda prompt to create and activate a Python environment named 'text_test_speech' with Python 3.9.
- 📁 Download the Python application files for the transcribing tool from the provided link and extract them to the desktop.
- 📝 Navigate to the Python folder using the Anaconda prompt and install required files by pasting the provided code.
- 🛠 Install additional packages like ffmpeg, forge, and setuptools-rust using the Anaconda prompt.
- 🎧 Choose a model size (tiny, small, medium, or large) for the transcription; medium is recommended for most audio.
- 🔍 The transcription process auto-detects the language if not specified; however, it can be set manually with the '--language' flag.
- 📑 The transcription results are saved as text files and can also be found in the sample folder.
- ⏱️ The first transcription may take longer due to downloading the model file, but subsequent transcriptions will be quicker.
- 🔄 To run the transcription again, open the Anaconda prompt, activate the environment, navigate to the sample audio folder, and execute the command with the appropriate file name and settings.
- 📚 For more details and options, refer to the help command provided in the script or visit the whisper documentation.
Q & A
What is the purpose of today's video?
-The purpose of the video is to teach viewers how to install a free audio to text transcriber, specifically the Whisper application by Open AI, on their Windows computer.
Which operating systems does the Whisper transcriber support?
-The Whisper transcriber supports both Windows 10 and Windows 11 operating systems.
What is the first step to install the Whisper transcriber?
-The first step is to install Python, and the video recommends using Anaconda for this installation.
How can one download and install Anaconda?
-To download and install Anaconda, one should Google 'Anaconda', click on the link, and then click on 'Get Additional Installers' to download the installer for Windows, Mac OS, or Linux.
What is the environment name used in the video for installing Python?
-The environment name used in the video is 'text_test_speech' with Python version 3.9.
How do you activate the Python environment created for the transcriber?
-To activate the environment, one should use the command 'conda activate text_test_speech' in the Anaconda prompt.
What is the process to navigate to the Python folder using the Anaconda prompt?
-To navigate to the Python folder, one should open the folder, copy its address, and then in the Anaconda prompt type 'cd' followed by a space and paste the copied address.
What additional files are required to be installed for the Whisper application?
-The additional files required for the Whisper application include 'ffmpz' and 'setuptools-rust', which can be installed using specific commands in the Anaconda prompt.
What are the different model sizes available for the Whisper transcriber?
-The different model sizes available for the Whisper transcriber are tiny, small, medium, and large, with each size offering varying levels of accuracy and speed.
How does one transcribe a sample audio file using the Whisper transcriber?
-To transcribe a sample audio file, one should navigate to the folder containing the audio file, use the appropriate command in the Anaconda prompt with the desired model size and language specified, and execute the command.
What are the output files generated after transcribing an audio file?
-After transcribing an audio file, the output files include a text file with the transcribed content, an SRT file with timestamps, and a VTT file.
How can one run the transcription process again after the initial setup?
-To run the transcription process again, one should open the Anaconda prompt, activate the 'text_test_speech' environment, navigate to the folder with the sample audio, and execute the appropriate command with the necessary parameters.
Outlines
💻 Installing Python and Anaconda for Transcriber Setup
The video begins with an introduction to installing a free audio to text transcriber, Whisper by Open AI, on a Windows computer. The process starts with downloading and installing Anaconda for Python, which is accessible on multiple operating systems including Windows, Mac OS, and Linux. The viewer is guided to create a Python environment using the Anaconda prompt with a specific command, and then activate this environment. The video also includes a step to download the Python application files and navigate to the folder containing these files. The installation of additional required files for the application is explained, followed by the installation of ffmpz and setup tools.rust, which are necessary for the proper functioning of the transcriber.
🎧 Transcribing Audio to Text Using Open AI Whisper
This paragraph demonstrates the process of transcribing audio to text using the Whisper model. It starts with a sample audio clip of a speech by a U.S. president, which the user intends to transcribe. The video then shows how to navigate to the folder containing the sample audio and execute a command in the Anaconda prompt to transcribe the audio using the 'medium' model. The command includes replacing placeholders with the actual audio file name and specifying the language as English. The video mentions that the first transcription might take longer due to the download of a model file, but subsequent transcriptions will be quicker. The result is a transcribed text file, and optionally, an SRT file with timestamps can also be generated. The video concludes with instructions on how to run the transcription process again, including activating the environment and navigating to the audio file location.
🔍 Detecting Language and Finalizing the Transcription Process
The final paragraph of the script confirms that the language has been detected during the transcription process. It reiterates that the transcription process will take some time, but once completed, all the necessary files will be available in the designated folder. The video ends with a note of thanks and an encouragement for viewers to explore and experiment with the transcription tool further. It also provides a help command for users who might need additional information or assistance with the tool.
Mindmap
Keywords
💡Audio to Text Transcriber
💡Anaconda
💡Python Environment
💡Conda
💡FFmpeg
💡Setup Tools
💡Model Sizes
💡Language Detection
💡Transcription
💡SRT File
💡VTT File
Highlights
Installing a free audio to text transcriber using Python application 'whisper' by Open AI.
The application is compatible with Windows 10 and 11, demonstrated on Windows 11.
First step is to install Python using Anaconda.
Anaconda can be downloaded for Windows, Mac OS, and Linux.
Using Anaconda prompt to create a Python environment.
Creating an environment named 'text_test_speech' with Python 3.9.
Activating the created Python environment.
Downloading the Python application files as a zip.
Extracting the downloaded files to the desktop.
Navigating to the Python folder using the Anaconda prompt.
Installing required files for the application.
Installing 'ffmpz' using conda.
Installing 'setuptools-rust' for additional functionality.
Selecting the 'medium' model for transcription accuracy and speed.
Using a sample audio clip for demonstration.
Transcribing the sample audio to text using the 'medium' model.
The transcription process may download a model file if required.
First transcription may take longer due to model file size.
Viewing the transcribed text and SRT file.
Transcription also creates a VTTD file.
Options for conversion include different model sizes and language specification.
Using the 'help' command for more information on usage.
Process of running the transcription after initial setup.
Auto-detection of language if not specified.
Final transcription results and file availability.
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