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 automated time-frequency domain audio crossfade


Automated Time-frequency Domain Audio Crossfades using Graph Cuts

Robinson, Kyle, Brown, Dan

arXiv.org Artificial Intelligence

Figure 1: This spectrogram shows overlapped segments of two music tracks after being combined and reconstructed along a per-frequency seam (bright yellow). The tracks were beat and tempo matched, then overlapped by 64 beats. EXTENDED ABSTRACT The problem of transitioning smoothly from one audio clip to another arises in many music consumption scenarios; especially as music consumption has moved from professionally curated and live-streamed radios to personal playback devices and services. Classically, transitioning from one song to another has been reliant on either pre-mixed transitions on recorded digital or physical media, hardware or software crossfading on the playback device, or professional transitions by a host or disk jockey (DJ). While options for software crossfading are ubiquitous on music streaming platforms and media players alike, these transitions pale in quality when compared to those manually applied by an audio engineer or DJ who can harmonically and rhythmically align tracks--and importantly--manually apply equalizer (EQ) filters during transitions.

  artificial intelligence, automated time-frequency domain audio crossfade, transition, (10 more...)
2301.1338
  Country: Europe > Netherlands > South Holland > Delft (0.05)
  Genre: Research Report (0.50)
  Industry: