AI-powered personalised audio: The next frontier in personalised experience

With the vast amount of data available, it can become difficult for people to filter through it all and discover what they're searching for. This is where Artificial Intelligence (AI) steps into play. It has the potential to revolutionise content creation by adapting it to each individual's unique requirements and interests. It is also revolutionising many diverse industries, and music streaming is no exception. While AI is changing the way people listen to audio, it is also enhancing the sound quality of their beloved films. This combination of existing AI algorithms and audio innovation improves sound quality while also creating personalised acoustic configurations.

Businesses are being transformed by utilising AI and machine learning technologies in their processes. As per a McKinsey report, around 70% of companies will adopt at least one AI technology in their operations by the year 2030. This growth will solely be accelerated by the promise of AI that it will augment and complement human capabilities.

Today, various leading streaming music platforms depend largely on AI algorithms to assess users' interests and provide personalised playlists and suggestions. These systems leverage advanced AI algorithms to sift through enormous music collections and user activity data, ultimately allowing highly customised user experiences.

Moreover, the technological mechanisms driving these AI-powered music recommendation systems are interesting. They predict user preferences by analysing patterns in user behaviour, song textual context, and music auditory features. For instance, Collaborative Filtering, leverages user activity patterns to suggest tracks that similar users have listened to. On the other hand, Natural Language Processing (NLP), analyses lyrics and other textual data to better comprehend song context. Additionally, Auditory Modelling entails an examination of the song's real auditory characteristics. These algorithms function both individually and collectively to provide extremely accurate and customised suggestions.

AI and machine learning are transforming how audio streaming services comprehend customer preferences and provide content. In addition, with the inclusion of these technologies, Content Delivery Networks (CDNs) have considerably improved.

• CDN optimisation: AI's primary responsibilities in CDN optimisation include managing network traffic, lowering latency and providing excellent audio streaming regardless of fluctuating network circumstances. Its employment in these areas affects how audio streams are provided, resulting in a better user experience along with greater platform loyalty.
• AI and predictive caching: AI also excels at predictive content caching. Its algorithms predict user behaviour, allowing for the pre-fetching and storing of material close to the user. This reduces delays and congestion in audio streaming, resulting in a smoother user experience. By anticipating what an individual will listen to next, AI guarantees that the information is ready to be provided immediately, lowering latency and enhancing overall streaming quality.
• Adaptive bitrate streaming: This technique optimises audio quality dependent on the user's network speed. AI constantly changes the stream quality in order to ensure a continuous listening experience without pauses, even when the network circumstances change. This in turn allows users to enjoy music streaming without interruption, regardless of network speed or reliability.

Besides improving content distribution, AI technologies are extensively used in the content production process for music streaming companies. The automated mastering services analyse and improve the audio quality of the tracks by using artificial intelligence algorithms. This includes regulating levels, adjusting equalisation, and compressing to offer an uninterrupted listening experience across several devices and sound systems.

Furthermore, AI not only improves but also creates sounds. AI-composed music tracks are becoming a reality, with algorithms capable of creating unique melodies, harmonies, and rhythms for a variety of genres and moods. This offers new possibilities for music streaming services, allowing them to provide subscribers with exclusive, AI-generated material. Numerous music streaming services use AI to curate creative material such as theme-based playlists and mood-specific listening experiences. For example, you may create a "Chill Out" playlist with tunes with slow tempos and relaxing harmonies, and a "Workout" playlist with lively, energetic tracks. This degree of personalisation elevates the music streaming experience by adapting it to the user's current mood or activities.

In recent years, AI has become a significant tool for organisations seeking to develop personalised content that connects with their target audience. Businesses may use multiple AI tools such as natural language processing and recommendation engines to develop more effective and interesting audio content that increases customer engagement and revenue.

While moving forward, future developments in AI and machine learning technology will offer more features, improved personalisation approaches, and novel content distribution ways for music streaming services. Presently, AI has the potential to accelerate cross-platform integrations and partnerships in the music business. By utilising it, music streaming platforms may deliver a more integrated and personalised listening experience by connecting to social networking platforms, fitness applications, and other digital services.

Another potential future for music platforms is the development of entirely new media formats that combine conventional storytelling concepts with immersive and interactive experiences. This might provide new chances for businesses to interact with audiences in novel ways. Thus, AI will be able to benefit the whole audio generation, distribution, and consumption ecosystem.

This article is authored by Sukhesh Madaan, CEO, Blaupunkt Audio India.