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Research Works
I am involved in writing code for quality assessment of AI generated music, researching AI generated music metrics.
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Designed and improved several harmonic and rhythmic metrics based on music theory to assess the quality of AI generated music, with respect to sequence structure, harmony and sound effect of a MIDI piece.
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Music MIDI copyright detection algorithms
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Implemented through Levenshtein metrics using C++, intergrated with Python using PyBind.
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Several improvements was made to boost the performance from original 10 hours to 8 minutes.
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Recently studying Deep-learning based music generation algorithms
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Mainly onTransformer-derived models including Transformer XL and GC Transformer.
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