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Margaret Mitchell is a computer scientist who works on algorithmic bias and fairness in machine learning.She is most well known for her work on automatically removing undesired biases concerning demographic groups from machine learning models, [2] as well as more transparent reporting of their intended use.
Hugging Face is a French-American company that develops computation tools for building applications using machine learning. It is known for its transformers library built for natural language processing applications.
Each speaker recognition system has two phases: enrollment and verification. During enrollment, the speaker's voice is recorded and typically a number of features are extracted to form a voice print, template, or model. In the verification phase, a speech sample or "utterance" is compared against a previously created voice print.
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In April 2023, Suno released their open-source text-to-speech and audio model called "Bark" on GitHub and Hugging Face, under the MIT License. [4] [5] On March 21, 2024, Suno released its v3 version for all users. [6] The new version allows users to create a limited number of 4-minute songs using a free account. [7]
Hugging Face's MarianMT is a prominent example, providing support for a wide range of language pairs, becoming a valuable tool for translation and global communication. [64] Another notable model, OpenNMT, offers a comprehensive toolkit for building high-quality, customized translation models, which are used in both academic research and ...
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Classification, face recognition, voice recognition 2018 [89] [90] S.R. Livingstone and F.A. Russo SCFace Color images of faces at various angles. Location of facial features extracted. Coordinates of features given. 4,160 Images, text Classification, face recognition 2011 [91] [92] M. Grgic et al. Yale Face Database