Audio Morphing for Percussive Hybrid Sound Generation

Primavera A, Piazza F, Reiss JD. Audio Morphing for Percussive Hybrid Sound Generation. In: AES Conference: 45th International Conference: Applications of Time-Frequency Processing in Audio. Audio Engineering Society; 2012. Paper 5-3. Available from: https://aes.org/publications/elibrary-page/?id=16185

@inproceedings{Primavera2012_16185,
  author = {Primavera, Andrea and Piazza, Francesco and Reiss, Joshua D.},
  title = {{Audio Morphing for Percussive Hybrid Sound Generation}},
  booktitle = {AES Conference: 45th International Conference: Applications of Time-Frequency Processing in Audio},
  note = {Paper 5-3},
  year = {2012},
  month = mar,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=16185}
}

TY  - CPAPER
TI  - Audio Morphing for Percussive Hybrid Sound Generation
AU  - Primavera, Andrea
AU  - Piazza, Francesco
AU  - Reiss, Joshua D.
T2  - AES Conference: 45th International Conference: Applications of Time-Frequency Processing in Audio
M1  - Paper 5-3
PY  - 2012
DA  - 2012/03/06
UR  - https://aes.org/publications/elibrary-page/?id=16185
PB  - Audio Engineering Society
LA  - en
AB  - The aim of audio morphing algorithms is to combine two or more sounds to create a new sound with intermediate timbre and duration. During the last two decades several efforts have been made to improve morphing algorithms in order to obtain more realistic and perceptually relevant sounds. In this paper we present an automatic audio morphing technique applied to percussive musical instruments. Based on preprocessing of the sound references in frequency domain and linear interpolation in time domain, the presented approach allows one to generate high quality hybrid sounds at a low computational cost. Several results are reported in order to show the effectiveness of the proposed approach in terms of audio quality and acoustic perception of the generated hybrid sounds, taking into consideration different percussive samples. mean opinion score and multidimensional scaling were used to compare the presented approach with existing state of the art techniques.
ER  -