Audio Tech Focus: AI Has Plenty of Potential - and Potential Pitfalls - for Broadcast Sports Most opine that AI has a place in production but so do people By Dan Daley, Audio Editor Wednesday, March 5, 2025 - 11:44 am
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-Artificial intelligence (AI) is either the greatest thing since sliced bread or the Y2K of the professional-audio sector. Or perhaps it could have an Oppenheimer effect: it could go either way, saving or destroying its creators while looking both menacing and alluring at the same time.
AI products designed for professional audio applications are already having an impact, such as Respeecher's use for ADR (automated dialog replacement) in films and video. In music, television, and live event production, AI is being used to automatically mix audio - when it's not being used to literally create it. In the process, it's also threatening the employment of the carbon-based creators who increasingly deploy it.
More than anything, however, AI's full potential for sound applications, including in broadcast and live sports production, remains ambiguous. A recent Sportico article about how the technology could be applied to FOX Sports' recent Super Bowl production placed AI prominently in its headline, only to then just vaguely reference the use of machine learning - considered a subset of AI - in an indeterminate future. AI has become its own meme, albeit a multibillion-dollar one.
SVG asked several audio gurus to assess AI's potential impacts when it comes to the sound for broadcast sports. Here's what they said.
The Need for Humans Quintar's Tom Sahara: Companies will need to invest before AI will consistently produce tangible results.
Tom Sahara, SVP, production technology, Quintar (a spatial-experience developer) and former VP, Turner Sports, sees both sides of the AI/audio coin. Its benefits include reducing the demands on an A1's attention during games by, for instance, monitoring signal levels and applying level management in a deterministic, predictable manner or automatically mixing input sources for secondary uses, such as in-ear-monitors, translations and alternate languages. It can even improve existing auto-mixing processes by incorporating data from external and non-audio sources, such as tally, router activity, record-device status, and GPS.
In addition, automated lip-sync and delay adjustments can be stored on a channel-by-channel basis along with time, playlist/clip ID, physical location (GPS), router settings, and other metadata, enabling video sources with synchronization errors to be corrected without re-editing or constructing discrete workflows. Further, he says, IP-enabled audio devices will accelerate the advance of AI/ML (artificial intelligence/machine learning) because the A/D conversion is expensive and not easily integrated into legacy workflows.
On the other hand, Sahara observes, there are myriad administrative, training, and support requirements that are not fully understood, and companies will need to invest before AI will consistently produce tangible results. For instance, training [AI-based] mixing and control agents to individual requirements can be expensive and time-consuming. We will have to see how DeepSeek-like approaches may affect this. And obtaining large numbers of training samples is difficult and can quickly exceed budget and time resources.
More ominously, he adds, Video hallucinations are easy to spot; however, audio is much more nuanced, making the verification process much more difficult. Humans still have to be involved.
Chris Fichera, VP, U.S. operations, Calrec, is another observer who sees both sides of the AI coin, citing its ability to provide audio processing in real time to manage announcer commentary, crowd noise, effects, and on-field sound as well as to automate EQ adjustments and create immersive 3D mixes based on real-time data. He does note the possible danger in becoming too reliant on the automation capabilities in a fast-moving, unpredictable sports show.
However, he points out, those capabilities could help alleviate the looming loss of experienced A1s for broadcast sports, as retirements increase and the cohort continues to age out. This could be very useful, particularly for an A1 with limited experience in doing a broadcast show.
A Glass Mostly Full
AudioShake's Suzanne Kirkland: AI tools will enhance [human expertise], freeing audio professionals to focus on storytelling and fan engagement rather than labor-intensive cleanup.
Some see a glass more than half full. In sports, says Suzanne Kirkland, business director, enterprise accounts, AudioShake, AI-driven tools like source separation, automixing, and voice cloning enable more-efficient workflows and unlock new content opportunities.
Source separation, our bread and butter at AudioShake, is helping leagues and broadcasters navigate the complexity of live sports audio, she says, where crowd noise, commentary, and in-game sounds compete for attention. Our dialog-isolation model enhances transcription accuracy by isolating clear speech from multiple speakers in noisy environments so that overlapping player, coach, and commentator dialog is captured with greater precision. That allows broadcasters to highlight what matters most, whether it's action on the field or the sidelines.
Music removal is another game-changer, helping teams and broadcasters avoid legal and monetization challenges, she continues. By stripping out copyrighted music while preserving speech and ambient sounds, our technology allows content to be shared more freely across platforms without risk of takedowns or licensing issues.
However, AI is still not a magic bullet that will alone transform the industry. It won't, she stresses, replace human expertise: AI
