Open Source Linux Speech Software
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Speech Software for Linux
View 331 business solutionsBrowse free open source Speech software and projects for Linux below. Use the toggles on the left to filter open source Speech software by OS, license, language, programming language, and project status.
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Auth0 for AI Agents now in GAConnect your AI agents to apps and data more securely, give users control over the actions AI agents can perform and the data they can access, and enable human confirmation for critical agent actions.
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G-P - Global EOR SolutionWith G-P's industry-leading Employer of Record (EOR) and Contractor solutions, you can hire, onboard and manage teams in 180+ countries — quickly and compliantly — without setting up entities.
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This is a Linux project that acts as a front end to cdparanoia, sox, and ffmpeg with the hope of making it incredibly simple to rip many audiobook cds into one mono, audiobook (m4b) format file for use in audio players capable of playing audiobooks.
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Portable GUI Ogg/Speex/FLAC audio encoder/player that can encode wave file and provides additional functionality such as audiofile tagging, html-album generator, cd-ripping, etc. Targeted to be used on Freebsd, Linux and win32 platforms and the frontends
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Listen to RSS news (from NetNewsWire), e-mail (from Mail), web pages (from Safari) and more on your iPod! This is an AppleScript Studio application that uses Mac OS X's built in text to speech technology to create audio files from these text documents an
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TLDP Audio Conversion This is an attempt to convert the Entire TLDP Project into audio format for expanded use and distribution
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Easy-to-use Business Software for the Waste Management Software IndustryDOP Software’s mission is to streamline waste and recycling business’ processes by providing them with dynamic, comprehensive software and services that increase productivity and quality of performance.
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de-ess
De-essing software to reduce sibilance in speech using TSP
This de-esser uses a novel approach called Temporal Sibilance Processing. The idea is to distinguish between fricatives and voiced sections of the speech signal by the number of zero crossings in time. Most of the speech file is left untouched (the samples are directly copied from source to destination). Only fricatives that are long enough and loud enough are filtered. The advantage of this approach over traditional approaches is that the clarity of the remaining speech is completely unaffected.
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