Audiotext
A desktop application that transcribes audio from files, microphone input or YouTube videos with the option to translate the content and create subtitles.
Table of Contents
- About the Project
- Getting Started
- Usage
- Transcription Language
- Transcription Method
- Audio Source
- Save Transcription
- Autosave
- Overwrite Existing Files
- Google Speech-To-Text API Options
- Google API Key
- Whisper API Options
- Whisper API Key
- Response Format
- Temperature
- Timestamp Granularities
- WhisperX Options
- Output File Types
- Translate to English
- Subtitle Options
- Advanced Options
- Troubleshooting
- Roadmap
- Authors
- Contributing
- Acknowledgments
- License
- Support
About the Project
Audiotext transcribes the audio from an audio file, video file, microphone input, directory, or YouTube video into any of the 99 different languages it supports. You can transcribe using the Google Speech-to-Text API, the Whisper API, or WhisperX. The last two methods can even translate the transcription or generate subtitles!
You can also choose the theme you like best. It can be dark, light, or the one configured in the system.
Dark
Light
Supported Languages
Click here to display
- Afrikaans - Albanian - Amharic - Arabic - Armenian - Assamese - Azerbaijan - Bashkir - Basque - Belarusian - Bengali - Bosnian - Breton - Bulgarian - Burmese - Catalan - Chinese - Chinese (Yue) - Croatian - Czech - Danish - Dutch - English - Estonian - Faroese - Farsi - Finnish - French - Galician - Georgian - German - Greek - Gujarati - Haitian - Hausa - Hawaiian - Hebrew - Hindi - Hungarian - Icelandic - Indonesian - Italian - Japanese - Javanese - Kannada - Kazakh - Khmer - Korean - Lao - Latin - Latvian - Lingala - Lithuanian - Luxembourgish - Macedonian - Malagasy - Malay - Malayalam - Maltese - Maori - Marathi - Mongolian - Nepali - Norwegian - Norwegian Nynorsk - Occitan - Pashto - Polish - Português - Punjabi - Romanian - Russian - Sanskrit - Serbian - Shona - Sindhi - Sinhala - Slovak - Slovenian - Somali - Spanish - Sundanese - Swahili - Swedish - Tagalog - Tajik - Tamil - Tatar - Telugu - Thai - Tibetan - Turkish - Turkmen - Ukrainian - Urdu - Uzbek - Vietnamese - Welsh - Yiddish - YorubaSupported File Types
Audio file formats
- `.aac` - `.flac` - `.mp3` - `.mpeg` - `.oga` - `.ogg` - `.opus` - `.wav` - `.wma`Video file formats
- `.3g2` - `.3gp2` - `.3gp` - `.3gpp2` - `.3gpp` - `.asf` - `.avi` - `.f4a` - `.f4b` - `.f4v` - `.flv` - `.m4a` - `.m4b` - `.m4r` - `.m4v` - `.mkv` - `.mov` - `.mp4` - `.ogv` - `.ogx` - `.webm` - `.wmv`Project Structure
ASCII folder structure
``` │ .gitignore │ audiotext.spec │ LICENSE │ README.md │ requirements.txt │ ├───.github │ │ CONTRIBUTING.md │ │ FUNDING.yml │ │ │ ├───ISSUE_TEMPLATE │ │ bug_report_template.md │ │ feature_request_template.md │ │ │ └───PULL_REQUEST_TEMPLATE │ pull_request_template.md │ ├───docs/ │ ├───res │ ├───img │ │ icon.ico │ │ │ └───locales │ │ main_controller.pot │ │ main_window.pot │ │ │ ├───en │ │ └───LC_MESSAGES │ │ app.mo │ │ app.po │ │ main_controller.po │ │ main_window.po │ │ │ └───es │ └───LC_MESSAGES │ app.mo │ app.po │ main_controller.po │ main_window.po │ └───src │ app.py │ ├───controllers │ __init__.py │ main_controller.py │ ├───handlers │ file_handler.py │ google_api_handler.py │ openai_api_handler.py │ whisperx_handler.py │ youtube_handler.py │ ├───interfaces │ transcribable.py │ ├───models │ │ __init__.py │ │ transcription.py │ │ │ └───config │ __init__.py │ config_subtitles.py │ config_system.py │ config_transcription.py │ config_whisper_api.py │ config_whisperx.py │ ├───utils │ __init__.py │ audio_utils.py │ config_manager.py │ constants.py │ dict_utils.py │ enums.py │ env_keys.py │ path_helper.py │ └───views │ __init__.py │ main_window.py │ └───custom_widgets __init__.py ctk_scrollable_dropdown/ ctk_input_dialog.py ```Built With
- CTkScrollableDropdown for the scrollable option menu to display the full list of supported languages.
- CustomTkinter for the GUI.
- moviepy for video processing, from which the program extracts the audio to be transcribed.
- OpenAI Python API library for using the Whisper API.
- PyAudio for recording microphone audio.
- pydub for audio processing.
- python-dotenv for handling environment variables.
- PyTorch for building and training neural networks.
- PyTorch-CUDA for enabling GPU support (CUDA) with PyTorch. CUDA is a parallel computing platform and application programming interface model created by NVIDIA.
- pytube for audio download of YouTube videos.
- SpeechRecognition for using the Google Speech-To-Text API.
- Torchaudio for audio processing tasks, including speech recognition and audio classification.
- WhisperX for fast automatic speech recognition. This product includes software developed by Max Bain. Uses faster-whisper, which is a reimplementation of OpenAI's Whisper model using CTranslate2.
Getting Started
Installation
-
Install FFmpeg to execute the program. Otherwise, it won't be able to process the audio files.
To check if you have it installed on your system, run
ffmpeg -version. It should return something similar to this:ffmpeg version 5.1.2-essentials_build-www.gyan.dev Copyright (c) 2000-2022 the FFmpeg developers built with gcc 12.1.0 (Rev2, Built by MSYS2 project) configuration: --enable-gpl --enable-version3 --enable-static --disable-w32threads --disable-autodetect --enable-fontconfig --enable-iconv --enable-gnutls --enable-libxml2 --enable-gmp --enable-lzma --enable-zlib --enable-libsrt --enable-libssh --enable-libzmq --enable-avisynth --enable-sdl2 --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxvid --enable-libaom --enable-libopenjpeg --enable-libvpx --enable-libass --enable-libfreetype --enable-libfribidi --enable-libvidstab --enable-libvmaf --enable-libzimg --enable-amf --enable-cuda-llvm --enable-cuvid --enable-ffnvcodec --enable-nvdec --enable-nvenc --enable-d3d11va --enable-dxva2 --enable-libmfx --enable-libgme --enable-libopenmpt --enable-libopencore-amrwb --enable-libmp3lame --enable-libtheora --enable-libvo-amrwbenc --enable-libgsm --enable-libopencore-amrnb --enable-libopus --enable-libspeex --enable-libvorbis --enable-librubberband libavutil 57. 28.100 / 57. 28.100 libavcodec 59. 37.100 / 59. 37.100 libavformat 59. 27.100 / 59. 27.100 libavdevice 59. 7.100 / 59. 7.100 libavfilter 8. 44.100 / 8. 44.100 libswscale 6. 7.100 / 6. 7.100 libswresample 4. 7.100 / 4. 7.100If the output is an error, it is because your system cannot find the
ffmpegsystem variable, which is probably because you don't have it installed on your system. To installffmpeg, open a command prompt and run one of the following commands, depending on your operating system:# on Ubuntu or Debian sudo apt update && sudo apt install ffmpeg # on Arch Linux sudo pacman -S ffmpeg # on MacOS using Homebrew (https://brew.sh/) brew install ffmpeg # on Windows using Chocolatey (https://chocolatey.org/) choco install ffmpeg # on Windows using Scoop (https://scoop.sh/) scoop install ffmpeg - Go to releases and download the latest.
- Decompress the downloaded file.
- Open the
audiotextfolder and double-click theAudiotextexecutable file.
Setting Up the Project Locally
- Clone the repository by running
git clone https://github.com/HenestrosaDev/audiotext.git. - Change the current working directory to
audiotextby runningcd audiotext. - (Optional but recommended) Create a Python virtual environment in the project root. If you're using
virtualenv, you would runvirtualenv venv. -
(Optional but recommended) Activate the virtual environment:
# on Windows . venv/Scripts/activate # if you get the error `FullyQualifiedErrorId : UnauthorizedAccess`, run this: Set-ExecutionPolicy Unrestricted -Scope Process # and then . venv/Scripts/activate # on macOS and Linux source venv/Scripts/activate - Run
pip install -r requirements.txtto install the dependencies. - (Optional) If you intend to contribute to the project, run
pip install -r requirements-dev.txtto install the development dependencies. - (Optional) If you followed step 6, run
pre-commit installto install the pre-commit hooks in your.git/directory. - Copy and paste the
.env.examplefile as.envto the root of the directory. - Run
python src/app.pyto start the program.
Notes
- You cannot generate a single executable file for this project with PyInstaller due to the dependency with the CustomTkinter package (reason here).
- For Apple Silicon Macs and Ubuntu users: An error occurs when trying to install the
pyaudiopackage. Here is a StackOverflow post explaining how to solve this issue. - I had to comment out the lines
pprint(response_text, indent=4)in therecognize_googlefunction from the__init__.pyfile of theSpeechRecognitionpackage to avoid opening a command line along with the GUI. Otherwise, the program would not be able to use the Google API transcription method becausepprintthrows an error if it cannot print to the CLI, preventing the code from generating the transcription. The same applies to the lines using theloggerpackage in themoviepy/audio/io/ffmpeg_audiowriterfile from themoviepypackage. There is also a change in the line 169 that changeslogger=loggertologger=Noneto avoid more errors related to opening the console.
Usage
Once you open the Audiotext executable file (explained in the Getting Started section), you'll see something like this:
Transcription Language
The target language for the transcription. If you use the Whisper API or the WhisperX transcription methods, you can set this to a language other than the one spoken in the audio in order to translate it to the selected language.
For example, to translate an English audio into French, you would set Transcription language to French, as shown in the video below:
https://github.com/user-attachments/assets/e68d9b90-3978-4ffb-9b62-bd3d57a1a33d
This is an unofficial way to perform translations, so be sure to double-check the generated transcription for errors.
Transcription Method
There are three transcription methods available in Audiotext:
-
Google Speech-To-Text API (hereafter referred to as Google API): Requires an Internet connection. It doesn't punctuate sentences (the punctuation is produced by Audiotext), and the quality of the resulting transcriptions often requires manual adjustment due to lower quality compared to the Whisper API or WhisperX. In its free tier, usage is limited to 60 minutes per month, but this limit can be extended by adding an API key.
-
Whisper API: Requires an Internet connection. This method is intended for people whose machines are not powerful enough to run WhisperX gracefully. It has fewer options than WhisperX, but the quality of the transcriptions is similar to those generated by the
large-v2model of Whisper X. However, you need to set an OpenAI API key to use this method. See the Whisper API Key section for more information. -
WhisperX: Selected by default. It doesn't require an Internet connection because the entire transcription process takes place locally on your computer. As a result, it's much more demanding of hardware resources than the other remote transcription methods. WhisperX can run on CPUs and CUDA GPUs, although it performs better on the latter. The quality of the transcription depends on the selected model size and computation type. In addition, WhisperX offers a wider range of features, including a more customizable subtitle generation process than the Whisper API and more output file types. It has no usage restrictions while remaining completely free.
Audio Source
You can transcribe from four different audio sources:
-
File (see image above): Click the file explorer icon to select the file you want to transcribe, or manually enter the path to the file in the
Pathinput field. You can transcribe audio from both audio and video files.Note that the file explorer has the
All supported filesoption selected by default. To select only audio files or video files, click the combo box in the lower right corner of the file explorer to change the file type, as marked in red in the following image:
-
Directory: Click the file explorer icon to select the directory containing the files you want to transcribe, or manually enter the path to the directory in the
Pathinput field. Note that theAutosaveoption is checked and cannot be unchecked because each file's transcription will automatically be saved in the same path as the source file.
For example, let's use the following directory as a reference:
└───files-to-transcribe │ paranoid-android.mp3 │ the-past-recedes.flac │ └───movies mulholland-dr-2001.avi seul-contre-tous-1998.mp4After transcribing the
files-to-transcribedirectory using WhisperX, with theOverwrite existing filesoption unchecked and the output file types.vttand.txtselected, the folder structure will look like this:└───files-to-transcribe │ paranoid-android.mp3 │ paranoid-android.txt │ paranoid-android.vtt │ the-past-recedes.flac │ the-past-recedes.txt │ the-past-recedes.vtt │ └───movies mulholland-dr-2001.avi mulholland-dr-2001.txt mulholland-dr-2001.vtt seul-contre-tous-1998.mp4 seul-contre-tous-1998.txt seul-contre-tous-1998.vttIf we transcribe the directory again with the Google API and the
Overwrite existing filesoption unchecked, Audiotext won't process any files because there are already.txtfiles corresponding to all the files in the directory. However, if we added the fileendors-toi.wavto the root offiles-to-transcribe, it would be the only file that would be processed because it doesn't have a.txtattached to it. The same would happen in the WhisperX scenario, sinceendors-toi.wavhas no transcription files generated.Note that if we check the
Overwrite existing filesoption, all files will be processed again and the existing transcription files will be overwritten. -
Microphone: To start recording, simply click the
Start recordingbutton to begin the process. The text of the button will change toStop recordingand its color will change to red. Click it to stop recording and generate the transcription.Here is a video demonstrating this feature:
https://github.com/user-attachments/assets/61f2173b-bcfb-4251-a910-0cf6b37598c6
Note that your operating system must recognize an input source, otherwise an error message will appear in the text box indicating that no input source was detected.
-
YouTube video: Requires an Internet connection to get the audio of the video. To generate the transcription, simply enter the URL of the video in the
YouTube video URLfield and click theGenerate transcriptionbutton when you are finished adjusting the settings.
Save Transcription
When you click on the Save transcription button, you'll be prompted for a file explorer where you can name the transcription file and select the path where you want to save it. Please note that any text entered or modified in the textbox WILL NOT be included in the saved transcription.
Autosave
Unchecked by default. If checked, the transcription will automatically be saved in the root of the folder where the file to transcribe is stored. If there are already existing files with the same name, they won't be overwritten. To do that, you'll need to check the Overwrite existing files option (see below).
Note that if you create a transcription using the Microphone or YouTube audio sources with the Autosave action enabled, the transcription files will be saved in the root of the audiotext-vX.X.X directory.
Overwrite Existing Files
This option can only be checked if the Autosave option is checked. If Overwrite existing files is checked, existing transcriptions in the root directory of the file to be transcribed will be overwritten when saving.
For example, let's use this directory as a reference:
└───audios
foo.mp3
foo.srt
foo.txtIf we transcribe the audio file foo.mp3 with the output file types .json, .txt and .srt and the Autosave and Overwrite existing files options checked, the files foo.srt and foo.txt will be overwritten and the file foo.json will be created.
On the other hand, if we transcribe the audio file foo.mp3 with the same output file types, with the option Autosave checked but without the option Overwrite existing files, the file foo.json will still be created, but the files foo.srt and foo.txt will remain unchanged.
Google Speech-To-Text API Options
The Google API options frame appears if the selected transcription method is Google API. See the Transcription Method section to know more about the Google API.
