Draft:SPPAS

speech annotation software From Wikipedia, the free encyclopedia

SPPAS is a free and open-source scientific software for the automatic annotation and analysis of speech recordings. It is used in speech and language research and provides tools for annotating, segmenting, analyzing, and editing speech data in multiple languages.[1][2]

  • Comment: In accordance with Wikipedia's Conflict of interest guideline, I disclose that I have a conflict of interest regarding the subject of this article. Bbigi (talk) 15:47, 30 March 2026 (UTC)


Original authorBrigitte Bigi
DeveloperBrigitte Bigi
Initial release14 June 2012
Written inPython
Quick facts SPPAS, Original author ...
SPPAS
Original authorBrigitte Bigi
DeveloperBrigitte Bigi
Initial release14 June 2012
Written inPython
Operating systemCross-platform
TypeSpeech annotation software
LicenseAGPL-3.0-or-later
Websitesppas.org
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Development of SPPAS began in 2011, and the software was first publicly released in 2012.[3]

History

SPPAS was initially developed for speech segmentation and progressively expanded to include additional annotation and analysis functions, as well as support for multiple languages.[3]

In the SPPAS 5 series, the software architecture was reorganized into a standalone application and a separate Python package. This version also introduced a browser-based dashboard as part of a transition toward a web-based user interface.[4]

Recognition

In 2022, SPPAS received an honourable mention by the jury in the French Open Science Awards for Open Source Research Software, awarded by the Ministry of Higher Education, Research and Innovation.[5][6]

SPPAS has been mentioned in external publications on speech annotation and alignment tools, including comparative work involving other systems such as Montreal Forced Aligner and WebMAUS.[7]

SPPAS was also cited by Square Enix in a 2024 SIGGRAPH Talks paper on lip-sync production for Final Fantasy VII Rebirth. The paper states that phoneme alignment by SPPAS had been used in the previous title, Final Fantasy VII Remake, before the newer machine-learning-based workflow was developed.[8]

References

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