HaoTech
AI-generated music, while technically adept and adherent to musical norms, raises questions among critics about its capability to showcase authentic human creativity and emotional depth. Rather than substituting human ingenuity, AI-generated music could serve as a supplement to it. The role of AI in the creation of music remains a subject of ongoing debate, but it is anticipated to instigate a revolution in the music industry.
INTRODUCTION
Artistic creation, be it a painting, a sculpture, a musical composition, or anything else, necessitates creativity and imagination. Until the arrival of AI technologies, this ability to imagine and create art was thought to be exclusive to humans. However, with the advent of generative art, machines too have shown the ability to craft art. By employing deep learning techniques, autonomous systems like AI can generate images, melodies, and other art forms based on the given inputs or prompts.
AI’S ROLE IN MUSIC CREATION
Artificial Intelligence (AI) can contribute to music creation in diverse ways. One of the most utilized methods involves leveraging machine learning algorithms, particularly deep neural networks, to analyze extensive datasets of existing music and then generate new compositions based on the findings.
Music creation via AI involves training the machine learning algorithm on a dataset of existing music, which could be an extensive library of songs in a specific genre or style. The algorithm identifies the patterns and structures in the music, such as the chords, melodies, beats, rhythms, and instrumentation, and then uses this understanding to create new music that mirrors the style and structure.
MUSIC REPRESENTATION FOR MACHINE LEARNING
The main hurdle in developing AI-based music is to convert music into a format that the machine learning model can understand. As the model processes information as a numerical vector, music must be represented as a series of numeric tokens that carry information about the rhythm, notes, timbre, and other pertinent data points. These tokens act as a musical representation that the AI system can process.
One way to train the model is by using MIDI files, a widely used protocol in the electronic music industry for transmitting musical information between digital devices. MIDI files are structured files that contain ordered information on notes, rhythm changes, BPM (beats per minute), and other associated data points, which can be treated as a natural language representation for training the model.
Many machine learning algorithms depend on using the raw audio data at each time step as input. These inputs are typically represented in the form of sequential input vectors, which are commonly used in natural language processing (NLP) to train the model. Then the model can predict the next token in a sequence at each timestep.
PLATFORMS FOR AI-GENERATED MUSIC
Artificial Intelligence (AI) is swiftly transforming the realm of music creation. AI-generated music platforms utilize machine learning algorithms to create unique and original music for videos, games, films, and various other media projects.
AIVA, Amper Music, Google’s Magenta, OpenAI’s MuseNet, Amadeus Code, and Jukedeck are among the leading AI-generated music platforms available today. Each platform has its unique features which cater to a variety of needs, whether you are a musician, a music composer, or a media creator.
LEGAL CONSIDERATIONS
The advent of AI in music creation has given rise to several legal issues that need resolution. Copyright ownership, licensing requirements, compensation for rights holders, and moral rights are some of the key legal matters associated with AI-generated music.
As AI’s role in music creation continues to expand, these legal aspects are expected to evolve and will be addressed by lawmakers and courts. It is vital for developers and users of AI-generated music to stay updated on the latest legal developments and seek legal counsel when required to ensure adherence to new legal terms and conditions.
CONCLUSION
While AI-generated music can exhibit technical excellence and alignment with established musical norms, some critics argue that it lacks the emotional depth and human creativity found in music created by humans. Hence, it is crucial to perceive AI-generated music as an enhancement to human creativity rather than a replacement for it. The role of AI in music creation remains a debatable topic, but it is poised to revolutionize the music industry in the foreseeable future. The evolving trajectory of AI technology in the realm of music is an intriguing prospect to observe.
