Search Results for "super audio"
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Showing 5 open source projects for "super audio"
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NovaSR
A lightning fast audio upsampler
NovaSR is an extremely lightweight and high-performance audio upsampling model that transforms low-quality 16 kHz audio into clearer, high-fidelity 48 kHz audio with remarkable speed and efficiency. At only about 50 KB in size, the model is orders of magnitude smaller than typical audio super-resolution networks, yet it achieves high quality and realtime performance thanks to its compact architecture and efficient convolutional design. -
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DocArray
The data structure for multimodal data
DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multimodal data with a Pythonic API. Door to multimodal world: super-expressive data structure for representing complicated/mixed/nested text, image, video, audio, 3D mesh data. The foundation data structure of Jina, CLIP-as-service, DALL·E Flow, DiscoArt etc. ... -
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VidCutter
A modern yet simple multi-platform video cutter and joiner
A modern, simple to use, constantly evolving and hella fast MEDIA CUTTER + JOINER w/ frame-accurate SmartCut technology, chapter support, media stream selection for audio + subtitle channels and blackdetect video filter support to automatically detect scene changes or skip commercials in digital TV recordings. Chapter support allows scene chapter names to be included in final media metadata. NOTE: results will only work in media players that support chapters. Flatpak release includes the... -
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DC-TTS
TensorFlow Implementation of DC-TTS: yet another text-to-speech model
DC-TTS is a TensorFlow implementation of the DC-TTS architecture, a fully convolutional text-to-speech system designed to be efficiently trainable while producing natural speech. It follows the “Efficiently Trainable Text-to-Speech System Based on Deep Convolutional Networks with Guided Attention” paper, but the author adapts and extends the design to make it practical for real experiments. The model is split into two networks: Text2Mel, which maps text to mel-spectrograms, and SSRN... -
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Cyn.in helps teams to build collaborative knowledge by sharing & discussing digital content within secure & unified application. It combines the capabilities of wikis, social network, blogs, files, microblogs, discussions into secure enterprise platform.
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