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3. how will you organise learning co dev toolkit - resource gr.f(ep)
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This was a university presentation for my second year strategy module. I needed to devise a campaign which would help to encourage more student's to undertake voluntary work within the university's radio station 107 Spark FM.
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This was a university presentation for my second year strategy module. I needed to devise a campaign which would help to encourage more student's to undertake voluntary work within the university's radio station 107 Spark FM.
Recruiting volunteers for Spark FM
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Recently, plenty of full-length concert videos have become available on video-sharing websites such as YouTube. As each video generally contains multiple songs, natural questions that arise include “what is the set list?” and “when does each song begin and end?” Indeed, many full concert videos on YouTube contain song lists and timecodes contributed by uploaders and viewers. However, newly uploaded content and videos of lesser-known artists typically lack this metadata. Manually labeling such metadata would be labor-intensive, and thus an automated solution is desirable. In this paper, we define a novel research problem, automatic set list segmentation of full concert videos, which calls for techniques in music information retrieval (MIR) such as audio fingerprinting, cover song identification, musical event detection, music alignment, and structural segmentation. Moreover, we propose a greedy approach that sequentially identifies a song from a database of studio versions and simultaneously estimates its probable boundaries in the concert. We conduct preliminary evaluations on a collection of 20 full concerts and 1,152 studio tracks. Our result demonstrates the effectiveness of the proposed greedy algorithm.
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Recently, plenty of full-length concert videos have become available on video-sharing websites such as YouTube. As each video generally contains multiple songs, natural questions that arise include “what is the set list?” and “when does each song begin and end?” Indeed, many full concert videos on YouTube contain song lists and timecodes contributed by uploaders and viewers. However, newly uploaded content and videos of lesser-known artists typically lack this metadata. Manually labeling such metadata would be labor-intensive, and thus an automated solution is desirable. In this paper, we define a novel research problem, automatic set list segmentation of full concert videos, which calls for techniques in music information retrieval (MIR) such as audio fingerprinting, cover song identification, musical event detection, music alignment, and structural segmentation. Moreover, we propose a greedy approach that sequentially identifies a song from a database of studio versions and simultaneously estimates its probable boundaries in the concert. We conduct preliminary evaluations on a collection of 20 full concerts and 1,152 studio tracks. Our result demonstrates the effectiveness of the proposed greedy algorithm.
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Automatic Set List Identification and Song Segmentation of Full-Length Concer...
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juko101
4. how will you know when you are achieving your aims co dev toolkit activity...
4. how will you know when you are achieving your aims co dev toolkit activity...
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4. how will you know when you are achieving your aims co dev toolkit activity...
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4. how will you know when you are achieving your aims co dev toolkit - resour...
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4. how will you know when you are achieving your aims co dev toolkit - resour...
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4. how will you know when you are achieving your aims co dev toolkit - resour...
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4. how will you know when you are achieving your aims co dev toolkit - resour...
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God is a creative God Gen 1:1. All that He created was “good”, could also be translated “beautiful”. God created man in His own image Gen 1:27. Maths helps us discover the beauty that God has created in His world and, in turn, create beautiful designs to serve and enrich the lives of others.
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