In the past two years, the maturity of AI technology has promoted the leap-forward development of AI applications. From the industrial application of high-end technology to the smart home, smart customer service, and smart navigation in daily life, AI has become the new darling of technological development in the new era.
At the same time, the range of AI that can be learned is not limited to pictures, actions, and sounds, but also has achieved quite good results in the creative fields of painting and composition.
In 2017, American singer Taryn Southern released the first album “I AM AI” composed by AI in history. The author put a melody of the main single “Break Free” into the AI music synthesizer Amper Music, the producer. Just select some basic parameter settings, such as rhythm instrument, key, etc., and chords can be automatically added, chorus generated, and almost completely inaudible to be composed by the application.
In fact, in the field of music creation, the application of AI has gradually matured, and the tools have become more and more extensive, covering AI lyrics, AI composition, audio synthesis and other aspects, bringing new development vitality to the music industry.
AI composition improves the efficiency of music creation
AI composition is not a mechanical single arrangement. In terms of creative principles, music is a regular arrangement, with long-term and short-term rules. AI designs hierarchical models based on these characteristics. Through deep learning and training of big data, the models can automatically generate songs similar to those made by human composers.
To put it simply, you do not need to master superb piano, guitar and other musical instrument performance skills, nor do you need to have profound knowledge of composition or music. With AI composition tools, you can generate corresponding music scores in a short period of time to achieve creative freedom. The threshold for composition has been greatly lowered.
Compared with the long cycle and high cost of manual creation, the high cost performance of AI composition can effectively help developers reduce costs and increase efficiency, and is suitable for music demand scenarios that do not require high creativity and require batch production. At this stage, AI composition technology is also gradually developing towards commercial applications, such as film and television drama soundtracks, video soundtracks, game soundtracks, online tool soundtracks, built-in products, etc.
How does AI composition work?
Like human learning, AI composition also needs to learn a large amount of music content in order to “create” new music works. To put it simply, it is to use deep learning algorithms to train AI with a large amount of music data. AI will build a mathematical model that reflects its understanding of music, and then use the model to create an original song in a relatively short period of time. .
At present, there are two main forms of AI composition, one is that the whole song is created out of thin air by AI, and the other is that AI continues to play on the basic tune after manually inputting the clip. No matter what form it is, it is inseparable from the process of “learning”. So, how does the machine “understand” the melody of music and then learn?
From the point of view of physics, the essence of sound is the transmission process of a series of vibration phenomena generated by the particle of the sound transmission medium. The beautiful music is the total effect of a series of particle vibrations.
Humans feel the effect of particle vibration through the eardrum and “music cells”; while AI, which can only read numbers, builds a bridge between “vibration” and “numbers” through MIDI.
MIDI (Musical Instrument Digital Interface), that is, the digital instrument interface, can also be simply understood as a digital score. It tells the keyboard, bass, drum kit, etc. how to sound at a certain time by storing the correspondence between time points and notes. Therefore, by converting a large number of MP3, WAV and other audio formats into MIDI files, sufficient learning data can be obtained.
Secondly, although MIDI has converted music into binary numbers, if you want AI to learn music in a refined way, MIDI needs to be further marked. Align the transcribed MIDI with the original audio, and then disassemble the melody of the synchronized MIDI file into basic elements such as pitch, length, intensity, chord, measure, etc., in order to finally convert it into a digital score that can be understood by machines.
Biaobei Technology has been deeply involved in the field of AI data services for many years. It has accumulated advanced technical capabilities and a large pool of music talents in data production, and has accumulated rich project experience in AI songs and AI musical instruments. In terms of the generation of accompaniment and arrangement, we can realize the AI soundtrack of different musical instruments such as piano, guitar, bass, drum kit, cello, violin, erhu, flute, guzheng, etc., and complete the corresponding labeling requirements.
With the continuous strengthening of machine algorithm learning, the development of AI music has also progressed rapidly in recent years, and its creative ability and quality of works have been greatly improved. Biaobei Technology will realize the implementation of more AI music scenarios through refined data services, and help AI music to move towards large-scale commercial applications.
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