AI in the Audio Industry – The Report for Radio & Podcasts
Artificial intelligence is no longer just an experiment in the audio industry – editorial teams, radio stations and podcast producers have been working with the technology on a daily basis for some time now. This is a good reason to take a closer look at which tools, companies and media organisations are working with AI. This report examines the Bavarian audio industry and its journey through the AI revolution.
What will the audio landscape of the future look like?
AI has already transformed the way audio content is produced. Thanks to smart tools and innovative projects, it’s now possible to remove background noise at the touch of a button, analyze the mood of radio listeners, and convert audio to text. Which companies and ideas are shaping the Bavarian audio industry? This report introduces them.
Update for the Audio Industry
You can find these topics on radio, podcasts, and AI in the report:
AI for Every Step of Production
We’ll show you how AI supports operations throughout the entire value chain:
- Concept: Faster idea development and automatic listener data analysis.
- Recording & Production: AI-based text-to-speech and shows without a host in the studio.
- Post-production: Background noise removal at the touch of a button, automatic transcription, and accessible content.
- Distribution: AI creates chapters and keywords and generates subtitles.
- Analysis: Emotion AI analyzes listeners’ moods.
How AI Can Measure Emotions and Gut Feelings
In this interview, Prof. Dagmar from audEERING discusses how AI can extract emotions, moods, and intentions from audio files. The company, based in Gilching near Munich, was founded in 2012 as a spin-off of the Technical University of Munich and has been conducting research in the field of Empathic AI ever since. Schuller explains why emotion recognition is an absolute milestone for AI and what this capability will bring us in the future.
Best Practices: These AI Projects Are Shaping Bavaria’s Audio Industry
When it comes to AI, the Bavarian audio industry has long since moved beyond the experimental phase. We’re highlighting four projects, ideas, and companies that rely on AI as a fundamental component. The applications are diverse: from a chatbot that gauges listener sentiment, to software used in disaster situations, to an AI-powered podcast and ad tool.
Curiosity, Not Hype: How BR Brings the Topic of AI into Its Newsrooms
The AI & Automation Lab at Bayerischer Rundfunk is the department responsible for ensuring that state-of-the-art AI technology is integrated into the media company’s day-to-day operations. Max Brandl is part of the innovation team and, in this interview, reveals which projects were a complete success, what lessons the team had to learn about AI, and what vision BR has for the future.
Studio quality at the touch of a button – from the comfort of your own home
Whilst moving images in particular have become increasingly better, simpler and higher-resolution in recent years, sound quality has long been neglected. Philipp Seeser has set out to change precisely that, and founded the company Xound. His software promises studio-quality sound at the touch of a button – accessible to everyone, easily from the comfort of their own home. In this interview, he explains what lies behind it.
The machine cannot recognise gut feelings. Nor can it recognise a guilty conscience. It recognises only what it has been taught and mimics the way humans would react. In certain areas, it outperforms humans because it has access to more data: recognising drunkenness, for example, or certain symptoms of illness. But anyone who knows what the system has been trained to recognise can also outwit it.
Prof. Dagmar Schuller, audEERING
It’s a good idea to approach AI with an open mind and a keen interest, but without getting carried away. It’s certainly a powerful force. The most important advice: keep at it, work with good people, and make the most of your own expertise.
Max Brandl, AI + Automation Lab at BR
At some point, radio programmes hosted entirely by AI will be the rule rather than the exception.
Valentina Ciardini, Fraunhofer IIS
The situation remains that audio quality is often the weakest link in content production. We now have smartphones with 4K cameras, but audio remains a challenge. This gave rise to the idea of using a machine-learning model dedicated solely to improving audio quality.
Philipp Seeser, Xound
