Search Results for "tagging" - Page 4
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Showing 85 open source projects for "tagging"
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Terz the incredible AutoTagger is a automated Audio File Tagger and File Renamer. It uses information provided by musicbrainz. By using context information Terz achieves very good results. Other features: show incomplete albums, search for Duplicates ...
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This software registers all the music files stored on CD's, hard drives, DVD's, etc. It will scan every media that you provide, and let you organize the files by artist, album, etc, with search and tagging facilities. Written in Python, GTK and MySQL.
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Pygme is an mplayer frontend written in Python/PyGTK. Pygme has a searchable media library (similar to winamp), a playlist and has ID3 tagging support. It uses sqlite through pysqlite bindings to maintain media lib and playlists.
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Mpyre is a Python front-end to cdparanoia and lame mp3, musepack, ogg vorbis and flac encoders, that includes id3 and apev2 tagging.
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madman administrates digitial music archives nicely: madman is a powerful digital music cataloging tool that is capable of flexible querying, tagging and organizing huge amounts of digital music.
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Platform independend filemanager for organizing, browsing and tagging large collections of mp3 files. Written in pyQt and therefore platform independend and highly customizable.
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Songer is an ID3 tagger designed for the ROX desktop that supports the drag-and-drop nature of ROX. It is designed to be a simple tagging utility. Songer currently only supports MP3s and ID3 version 1 tags. Future support of ID3v2 and OGG files is planne
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This library and tools help you to keep tags for files in an external database. As few external dependencies as possible are needed, making it a lightweight file tagging solution.
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Foton is a photo manager developed with the usage of python, pyqt and exiv2. Main features I hope to implement are: - A good tag management an organizing of pictures, tagging of people and in the future connection to facebook... Very early stage..
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Dia-1.6B
Dia-1.6B generates lifelike English dialogue and vocal expressions
Dia-1.6B is a 1.6 billion parameter text-to-speech model by Nari Labs that generates high-fidelity dialogue directly from transcripts. Designed for realistic vocal performance, Dia supports expressive features like emotion, tone control, and non-verbal cues such as laughter, coughing, or sighs. The model accepts speaker conditioning through audio prompts, allowing limited voice cloning and speaker consistency across generations. It is optimized for English and built for real-time performance...
