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Found 7 papers, 4 papers with code
Documenting use cases in the affective computing domain using Unified Modeling Language
The study of the ethical impact of AI and the design of trustworthy systems needs the analysis of the scenarios where AI systems are used, which is related to the software engineering concept of "use case" and the "intended purpose" legal term.
Monitoring Diversity of AI Conferences: Lessons Learnt and Future Challenges in the DivinAI Project
DivinAI is an open and collaborative initiative promoted by the European Commission's Joint Research Centre to measure and monitor diversity indicators related to AI conferences, with special focus on gender balance, geographical representation, and presence of academia vs companies.
Deep Learning Based Source Separation Applied To Choir Ensembles
However, most of the research has been focused on a typical case which consists in separating vocal, percussion and bass sources from a mixture, each of which has a distinct spectral structure.
Content Based Singing Voice Extraction From a Musical Mixture
We present a deep learning based methodology for extracting the singing voice signal from a musical mixture based on the underlying linguistic content.
Artificial intelligence in medicine and healthcare: a review and classification of current and near-future applications and their ethical and social Impact
This paper provides an overview of the current and near-future applications of Artificial Intelligence (AI) in Medicine and Health Care and presents a classification according to their ethical and societal aspects, potential benefits and pitfalls, and issues that can be considered controversial and are not deeply discussed in the literature.
WGANSing: A Multi-Voice Singing Voice Synthesizer Based on the Wasserstein-GAN
We present a deep neural network based singing voice synthesizer, inspired by the Deep Convolutions Generative Adversarial Networks (DCGAN) architecture and optimized using the Wasserstein-GAN algorithm.
Sound Audio and Speech Processing
End-to-End Sound Source Separation Conditioned On Instrument Labels
Can we perform an end-to-end music source separation with a variable number of sources using a deep learning model?
