Harnessing Machine Learning to Solve TV’s Biggest Sound Problem — Dialogue Intelligibility

For years, a frustrating paradox has plagued the television viewing experience. As screens grow larger and visuals become sharper, the sound quality, particularly dialogue intelligibility — how clearly and easily spoken words can be understood — has often lagged. Viewers are left annoyed, struggling to understand dialogue, which detracts from their enjoyment. Nothing pulls someone out of a story faster than straining to catch what a character just said. However, this challenge presents an opportunity for TV manufacturers to differentiate their products and meet consumer demand for a more immersive and accessible audio experience. How? Audio machine learning (ML).

The shortcomings of traditional dialogue enhancement methods

Traditional methods of dialogue enhancement, while helpful to a degree, have often fallen short of delivering a truly satisfying audio experience:

• Dynamic range compression (DRC), a common audio processing technique that makes loud sounds quieter and quiet sounds louder, can introduce unwanted “pumping” effects where the volume seems to fluctuate unnaturally, or worse, suppress the dialogue it’s intended to enhance.
  
  
• Dialogue enhancement filters, which boost frequencies associated with speech (typically between 125Hz and 5,000Hz), can sometimes improve clarity, but they also impact other audio elements like background music and sound effects, resulting in a less balanced and immersive soundscape.
  
  
• Dialogue boosting technologies, which provide alternative audio mixes optimized for clearer speech, are often limited to specific platforms, languages and content, restricting their effectiveness.
  
  
• While personalization holds promise, creating tailored soundtracks based on individual preferences requires separating dialogue, music and effects (DME) into discrete tracks — a process that, though effective, demands significant storage and is impractical for every viewing scenario.

The power of machine learning for dialogue enhancement

ML offers a powerful new way to improve dialogue that overcomes these limitations. Unlike digital signal processing (DSP) techniques, ML models can be trained to recognize acoustic patterns and distinguish between dialogue, music and sound effects with remarkable accuracy. This level of understanding allows for a more nuanced and precise approach to enhancing dialogue clarity.

By learning the complex interplay between these audio elements, ML algorithms can intelligently “unmix” the audio, creating a clearer separation between speech and background sounds. This process offers greater flexibility for personalization and customization, allowing viewers to tailor their audio experience to specific preferences and listening environments. It also minimizes any unwanted side effects, preserving the integrity of the overall soundscape while significantly improving dialogue intelligibility.

DTS Clear Dialogue: A new era of audio clarity

DTS Clear Dialogue is a prime example of how audio ML can revolutionize the television viewing experience. This solution leverages on-device AI-based audio processing and a deep learning network trained on diverse datasets to ensure its effectiveness across a wide range of content and listening scenarios. This extensive training allows the model to:

• Identify, separate and enhance dialogue to increase intelligibility
  
  
• Personalize audio experiences by allowing customers to control the dialogue volume level on demand
  
  
• Deliver customizable, consistent and reliable audio performance regardless of the source material

DTS Clear Dialogue tackles dialogue intelligibility challenges head-on by addressing the interplay between speech, background music and effects. By isolating and enhancing dialogue, this technology improves the clarity of spoken language, ensuring viewers can easily follow conversations without straining to hear or constantly adjusting the volume. With clean sound comes a better viewing experience, drawing audiences deeper into the story and letting them appreciate the subtleties of the audio mix.

A strategic advantage for TV manufacturers

Embracing AI-powered audio solutions like DTS Clear Dialogue is not just a technical upgrade — it’s a strategic move for TV manufacturers. By addressing one of the most common viewer complaints — poor dialogue intelligibility — manufacturers can enhance customer satisfaction and loyalty. In a competitive market, superior audio quality is a key differentiator.

AI-powered solutions are highly scalable and compatible with existing hardware, making them a practical choice for manufacturers looking to future-proof products. They deliver a user-centric experience that prioritizes both accessibility and personalization, catering to the needs and preferences of today’s viewers. By investing in these cutting-edge technologies, manufacturers can exceed evolving consumer demands, positioning themselves at the forefront of innovation in the television industry.

Ready to revolutionize audio and deliver frustration-free viewing experiences? Discover how DTS Clear Dialogue can help you stand out with unmatched dialogue intelligibility.