AI Voiceover Is Often More Time-Consuming Than Human Voice Talent

Written by Nigel Kettle

While Artificial Intelligence (AI) has made significant strides in automating voiceover generation, despite its promise, using AI for voiceovers is often much more time-consuming than working with a skilled human voice actor. This is primarily due to the nuanced and complex nature of human speech, which AI still struggles to replicate effectively.

One of the most prominent issues with AI-generated voiceovers is the inability to consistently deliver correct inflections and emotional tones. Human voice actors naturally modulate their pitch, pace, and volume to convey meaning, emphasis, and emotion. AI, on the other hand, frequently produces speech that sounds flat, robotic, or unnatural. Correcting these inflection errors requires multiple rounds of adjustments, manual tweaking, and sometimes re-generating entire segments, significantly increasing the time needed to achieve a satisfactory result.

Foreign languages, such as Chinese, Japanese, Arabic, and Urdu, further compound the problem because they are inherently more complex.  Here are some things to bear in mind.

Pronunciation of Names: A Persistent Challenge

AI voiceover systems often mispronounce people’s names, business names, and other unique terms. Unlike humans, who can be coached or provided with phonetic guidance, AI models may not have access to correct pronunciations, especially for uncommon or non-English names. This results in awkward or incorrect renderings that require manual intervention, custom phonetic spelling inputs, and repeated trial-and-error to fix.

Multilingual Voiceovers: Complexities and Limitations

Handling voiceovers in various languages introduces additional complications for AI. Many AI systems are trained primarily on widely spoken languages and may lack the data or linguistic sophistication to handle less common languages, dialects, or regional accents. This can lead to incorrect grammar, unnatural intonation, and mispronunciation of culturally specific terms. Achieving high-quality multilingual voiceovers with AI demands extensive localization work, further increasing the time and resources required.

Additional Issues with AI Voiceover Technology

• Contextual Understanding: AI struggles with interpreting the context in which a line is delivered, which can result in inappropriate emphasis or tone.

• Customization Limitations: Fine-tuning AI voices for specific brand personas or character traits is often complex and time-intensive.

• Editing and Post-Processing: AI-generated audio frequently needs significant editing to remove artifacts, correct pacing, or splice together usable clips.

So while AI voiceover technology offers exciting possibilities, its current limitations make producing high-quality, natural-sounding voiceovers often more time-consuming than working with human voice actors. Inflection, pronunciation, multilingual capabilities, and contextual understanding remain significant hurdles. As AI continues to evolve, it may close these gaps, but for now, the expertise and efficiency of human voice talent remain unmatched in most professional settings.

For down-and-dirty VO jobs, AI is great. If you are trying to achieve a high-quality AI recording that can pass for a human, the job will take you longer than if you used a real human. The issue we face as a post-production company is that clients want to pay less for AI-VO services but still get a high-quality, human-like recording.  And yes, depending on the material, it can be done, but it will cost you more than using humans.  The challenge is, why pay more for less?