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His programs Project 1 and Project 2 are examples of this kind of software. Later, he extended the same kind of principles into the realm of synthesis, enabling the computer to produce the sound directly. SSP is an example of a program which performs this kind of function.
Examples of this branch of research would include digitizing scores ranging from 15th Century neumenal notation to contemporary Western music notation. Like sheet music data, symbolic data refers to musical notation in a digital format, but symbolic data is not human readable and is encoded in order to be parsed by a computer.
This is used in sound cards that support both audio in and out, for instance. Hardware audio codecs send and receive digital data using buses such as AC-Link, I²S, SPI, I²C, etc. Most commonly the digital data is linear PCM, and this is the only format that most codecs support, but some legacy codecs support other formats such as G.711 for ...
Current research includes the application of AI in music composition, performance, theory and digital sound processing. Erwin Panofksy proposed that in all art, there existed three levels of meaning: primary meaning, or the natural subject; secondary meaning, or the conventional subject; and tertiary meaning, the intrinsic content of the subject.
Scores give a clear and logical description of music from which to work, but access to sheet music, whether digital or otherwise, is often impractical. MIDI music has also been used for similar reasons, but some data is lost in the conversion to MIDI from any other format, unless the music was written with the MIDI standards in mind, which is rare.
Digital audio is a representation of sound recorded in, or converted into, digital form. In digital audio, the sound wave of the audio signal is typically encoded as numerical samples in a continuous sequence. For example, in CD audio, samples are taken 44,100 times per second, each with 16-bit resolution.
Other examples of generative music technology include the use of sensors connected to computer and artificial intelligence to generate music based on captured data, such as environmental factors, the movements of dancers, or physical inputs from a digital device such as a mouse or game controller.
The usual process for data sonification is directing digital media of a dataset through a software synthesizer and into a digital-to-analog converter to produce sound for humans to experience. [ 1 ] [ 2 ] [ 3 ] Benefits to interpreting data through sonification include accessibility, pattern recognition, education, and artistic expression.