{'fraction_non_alphanumeric': 0.020948860135551448, 'fraction_numerical': 0.011090573012939002, 'mean_word_length': 5.222222222222222, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
The evolution of drum modes with strike intensity: Analysis and synthesis using the discrete cosine transform.

The synthesis of convincing acoustic drum sounds remains an open problem. In this paper, a method for analysing and synthesising pitch glide in drums is proposed, whereby the discrete cosine transform (DCT) of an unwindowed drum sound is modelled. This is an extension of the scheme initially proposed by Kirby and Sandler [(2020). Proceedings of the 23rd International Conference on Digital Audio Effects, Vienna, Austria, pp. 155-162], which was able to reproduce key components of drum sounds accurately enough that they could not be distinguished from the reference samples. Here, drum modes were analysed in greater detail for a tom-tom struck at 67 different intensities to investigate their evolution with strike velocity. A clear evolution was observed in the DCT features, and interpolation was used to synthesise the modes of intermediate velocity. These synthesised modes were evaluated objectively through null testing, which showed that a continuous blending of strike velocities could be achieved throughout the data set. An AB listening test was also performed, where 20 participants attempted to distinguish between pairs of real and synthesised sounds. Exactly 50% accuracy was achieved overall, which demonstrates that the synthesised samples were deemed to sound as realistic as genuine samples. These results demonstrate that the DCT representation is a valuable framework for analysis and synthesis of drum sounds. It is also likely that this approach could be applied to other instruments.