How to Make AI Cover Songs: Artificial Intelligence in Music

How to Make AI Cover Songs: Artificial Intelligence in Music

By Luca Fanicchia

The intersection of technology and music has given rise to some truly remarkable innovations. One such innovation that has taken the music industry by storm is the ability of Artificial Intelligence (AI) to create cover songs. AI has revolutionized the way we approach music production, allowing both amateur and professional musicians to explore new creative horizons. In this article, we will delve into the world of AI-generated cover songs and provide you with a step-by-step guide on how to make AI cover songs of your own.

Mastering AI: A Beginner’s Guide to Understanding and Utilizing Artificial Intelligence

Understanding AI-Generated Music

Before we dive into the process, it’s essential to understand what AI-generated music is and how it works. AI cover songs are created using machine learning models, particularly those based on deep neural networks. These models are trained on vast datasets of existing songs, enabling them to analyze patterns in music, such as melodies, harmonies, and rhythms.

AI-generated music is a product of pattern recognition and generation. These AI systems can analyze and replicate musical patterns with a level of complexity that would be incredibly time-consuming for human musicians to achieve. They can generate original compositions or reinterpret existing songs in various musical styles.

Step 1: Choose the Right AI Tool

The first step in creating AI cover songs is selecting the appropriate AI tool. Several AI-powered platforms and software applications have emerged, making it easier for musicians and enthusiasts to explore AI music generation. Here are some popular options:

  • OpenAI’s MuseNet: MuseNet is a versatile AI tool capable of composing music in various styles and genres. Its neural networks have been trained on an extensive library of classical and contemporary music, making it an excellent choice for generating cover songs with a unique twist.
  • Amper Music: Amper Music offers an easy-to-use platform for AI music composition. It allows you to input your preferences, such as mood, tempo, and instrumentation, and create music that suits your vision. It’s particularly useful for those looking for quick and customizable results.
  • Google’s Magenta Studio: Magenta Studio is an open-source platform that offers a range of AI-powered music creation tools. It’s ideal for musicians and developers who want more control over the AI’s creative process. You can experiment with different models and fine-tune the AI’s output to match your artistic preferences.

Step 2: Select the Song and Style

Once you’ve chosen your AI tool, it’s time to decide on the song you want to cover and the style you want to apply. This step allows you to infuse your creative input into the AI-generated cover. Consider these factors when selecting a song and style:

  • Song Choice: You can choose a classic song with a timeless melody or a contemporary hit that resonates with your audience. Keep in mind that the AI will reinterpret the song, so select one that you have a strong emotional connection with or that you believe has potential in a new musical context.
  • Musical Style: Determine the musical style or genre in which you want the AI to reinterpret the song. For example, you can transform a rock ballad into a jazz masterpiece or give a pop hit a classical twist. The choice of style will significantly influence the final result.

Step 3: Train the AI Model

After selecting the song and style, you’ll need to configure the AI model accordingly. Most AI tools will require you to input parameters such as tempo, key, and instrumentation. This step helps tailor the AI’s output to match your desired musical direction.

  • Tempo: Adjust the tempo to match the desired mood of the cover song. Slower tempos can create a more relaxed and emotive atmosphere, while faster tempos can infuse energy and excitement.
  • Key: Select the key that complements the song’s melody and lyrics. The key determines the musical scale and can significantly impact the emotional resonance of the cover.
  • Instrumentation: Specify the instruments you want to be used in the AI-generated arrangement. This is where you can get creative by experimenting with different combinations of instruments. For instance, you can mix traditional instruments with electronic elements for a unique sound.

Step 4: Refine and Customize

While AI can generate music autonomously, you may want to take the opportunity to refine and customize the output. This step allows you to add your personal touch and artistic flair to the AI-generated composition:

  • Melodies and Harmonies: Review the melodies and harmonies generated by the AI. You can make adjustments to ensure that they align with your artistic vision. For instance, you might want to add embellishments, variations, or new melodies to make the cover more distinctive.
  • Lyrics: If you plan to include vocals in your cover song, you can write original lyrics or modify existing ones to suit the new musical arrangement. This step is crucial for making the cover song feel truly unique.
  • Arrangement: Experiment with the arrangement of the instruments and musical elements. Consider the dynamics, transitions, and overall structure of the song. You can add instrumental solos, breakdowns, or other creative elements to enhance the listening experience.

Step 5: Record and Produce

With the AI-generated music in hand, it’s time to bring it to life. You can use digital audio workstations (DAWs) and music production software to record and produce the cover song. Here are the key steps in this phase:

  • Recording: If you’re adding vocals, record them in a soundproof environment with high-quality microphones. Ensure that the vocal performance matches the emotion and style of the cover song.
  • Instrumentation: Record any live instruments that you plan to include in the cover. You can also use virtual instruments and MIDI controllers to recreate the AI-generated instrumentals.
  • Mixing and Mastering: Use audio mixing software to balance the levels of each instrument and vocal track. Apply effects such as equalization, reverb, and compression to achieve a polished sound. Finally, master the track to ensure that it’s ready for distribution and playback on various platforms.

Step 6: Share and Collaborate

Once you’ve produced your AI cover song, it’s time to share it with the world. Utilize various platforms and strategies to reach a broader audience:

  • Music Streaming Platforms: Upload your cover song to popular music streaming platforms like Spotify, Apple Music, and YouTube. Ensure that you follow the platform’s guidelines for music distribution.
  • Social Media: Share snippets, teasers, and behind-the-scenes content on social media platforms to create excitement and engagement among your followers. Consider running targeted ad campaigns to reach a wider audience.
  • Collaboration: Collaborate with other musicians or artists to add a unique human touch to your AI-generated creation. Live performances, music videos, or joint projects can help generate buzz and expand your reach.

When Will Artificial Intelligence Surpass Human Intelligence

Challenges and Limitations of AI in Music

While the integration of Artificial Intelligence (AI) in music creation and production has brought about remarkable advancements, it is not without its challenges and limitations. It’s essential to understand these constraints to navigate the landscape of AI-generated music effectively:

1. Lack of Creative Intuition

One of the primary limitations of AI in music is its inability to possess the genuine creative intuition and emotional depth that human musicians bring to their work. AI systems rely on patterns and data, which means that while they can mimic existing styles and genres, they may struggle to produce truly groundbreaking or emotionally resonant compositions. AI-generated music often lacks the depth of expression that human musicians can convey.

2. Dependence on Training Data

AI models used for music generation depend heavily on the quality and quantity of their training data. Limited or biased datasets can result in AI-generated music that lacks diversity or originality. Moreover, training AI models requires a substantial amount of data, which may not always be readily available for niche or lesser-known music genres.

3. Copyright and Legal Concerns

The use of AI in creating cover songs or reinterpretations of existing music raises significant copyright and legal concerns. Determining the legality of AI-generated music, obtaining licenses, and navigating the complexities of intellectual property rights can be challenging. Musicians and creators must be diligent in ensuring that their AI-generated work complies with copyright laws.

4. Risk of Homogenization

As AI becomes more prevalent in music production, there is a risk of music becoming homogenized. AI-generated music may follow popular trends and formulas, leading to a sameness in musical content. This can stifle diversity and creativity in the music industry, potentially limiting the discovery of unique and innovative musical styles.

5. Ethical Considerations

The use of AI in music raises ethical questions related to authorship and artistic integrity. Determining the credit and recognition due to AI systems, as well as the role of human creators in AI-assisted music, is an ongoing debate. Ethical considerations also extend to issues such as transparency in disclosing AI involvement in music production.

6. Bias in AI Models

AI models, like any other technology, can inherit biases present in their training data. This bias can manifest in AI-generated music, affecting the choice of melodies, harmonies, and even lyrics. Musicians must be vigilant in identifying and addressing bias in AI-generated compositions to ensure that their music does not inadvertently perpetuate stereotypes or prejudices.

7. The Limitations of AI Instruments

While AI can generate music, it is not capable of playing physical instruments or replicating the nuances of human musicianship. AI instruments may lack the subtleties and dynamics that come from a skilled human performer. Consequently, AI-generated music may still require human musicians for certain elements, especially in live performances.

8. Commercial Viability

Although AI-generated music has its merits, it may face challenges in gaining commercial acceptance and popularity. The music industry and audiences can be resistant to AI-created content, preferring the authenticity and emotional connection associated with human musicians.

Demystifying AI: Understanding Different Types of Artificial Intelligence


The fusion of AI and music has opened up exciting possibilities for musicians and music enthusiasts alike. Creating AI cover songs is not only a creative endeavor but also an exploration of the limitless potential of technology in the world of music. By following the steps outlined in this guide and experimenting with different AI tools, you can embark on a musical journey that transcends conventional boundaries. With dedication and innovation, you might just create the next viral AI cover sensation.

So, go ahead and harness the power of AI to breathe new life into classic songs or reimagine modern