We gathered a total of 300 answers and overall people answered positively to all questions, which confirms our approach was successful and worth further exploring. They evaluated whether people considered our musical artifacts music, if they thought the artifacts had quality, if they considered the artifacts 'novel', if they liked the artifacts, and lastly if they were able to relate the artifacts with the image in which they were inspired. The three versions were evaluated for six different images by conducting surveys. The automatic version maps features from the image into musical features non-deterministically the co-created version adds harmony lines manually composed by us to the automatic version finally, the genetic version applies a genetic algorithm to a mixed population of automatic and co-created artifacts. Three different musical arti-facts are generated: an automatic version, a co-created version, and a genetic version. Results of this mapping are fed to a Genetic Algorithm (GA) to try to better model the creative process and produce more interesting results. It uses images as source of inspiration and begins by implementing a possible translation between visual and musical features. MuSyFI is a system that tries to model an inspirational computational creative process. In comparison to state-of-the-art black-box attacks, our attack is more effective at generating adversarial examples and achieves a higher attack success rate on all three baseline models. We conduct a parameter study outlining the impact the number and type of shapes have on the proposed attack's performance. To evaluate the effectiveness of our proposed method, we attack three state-of-the-art image classification models trained on the CIFAR-10 dataset in a targeted manner. Different from most prevalent black-box attacks that make use of substitute models or gradient estimation, this paper proposes a gradient-free attack by using a concept of evolutionary art to generate adversarial examples that iteratively evolves a set of overlapping transparent shapes. A more realistic assumption is the black-box scenario where an attacker only has access to the targeted model by querying some input and observing its predicted class probabilities. Many works go with a white-box attack that assumes total access to the targeted model including its architecture and gradients. Results show that the proposed algorithm performs better than conventional genetic algorithm.ĭeep neural networks (DNNs) have achieved state-of-the-art performance in many tasks but have shown extreme vulnerabilities to attacks generated by adversarial examples. In the end, a comparative analysis is conducted to show the efficacy of the proposed model. PySynth, a simple music synthesizer, is chosen to convert music into wave file format. The rhythm is generated using Bresenham’s line drawing algorithm, which has been modified to adapt different time signature with changing beats. To create a proper sequence of notes, we used genetic algorithm with suitably formulated crossover and mutation operators. The type of music composed in this work is monophonic, which includes melody and rhythm. Moreover, the user can also input any desired motif (a short piece of melody) and generate a melody that includes the motif.
The proposed method gives flexibility to change the musical parameters, namely time signature, range and scale. In this paper, a new approach for music composition is proposed that differs from previous methods of generating music with predefined musical parameters. The role of machine in automatic generation of creative artworks, like music, is still an explorable area. I will continue to delve into this, but in the meantime does anyone have a possible explanation, suggestion or remedy? Thanks in advance.Music composition is one of the oldest artistic pursuits.
I never adjusted any sound card or application setting. All of this happened suddenly, and without provocation. To add insult to injury, now, none of my previous projects have sound! And, recording additional tracks is disabled. When I click on "Master" in the track listing to attempt a fix, there seems to be no way to change settings. The items listed below will be silent in your project until their outputs are assigned to an appropriate hardware output" and "Master"is indicated below the message-still appears at the onset while opening the project. But the " Silent Bus Detected" message-the one that reads " The following tracks and buses are currently assigned to a silent hardware output.
#Jammer pro 6 vs band in a box driver
In so far as the aforementioned current project is concerned the first error pop-up ( "There are no audio devices for the current driver model on your system.etc.) I indicated in my initial message now does not appear. Even after uninstalling and re-installing Music Creator 7, problems still abound. This situation has officially become frustrating.
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