Exploring the Differences Between AI-Based TTS and TTS Automation in Course Development (August 2023)

I recently had a conversation with a colleague about the differences between automation and AI, which got me thinking about how this relates to a feature called text-to-speech (TTS). TTS can save a significant amount of time when developing eLearning courses, but what's the difference between automation and AI?

Automation systems follow pre-defined rules to execute tasks without decision-making capabilities. In contrast, AI systems can handle complex tasks in dynamic environments, make decisions and take actions based on data analysis, and learn from experience.

There are two methods for text-to-speech: TTS automation and AI-based text-to-speech.

TTS automation uses rule-based algorithms and pre-recorded voice recordings to convert written text into speech. It concatenates pre-recorded segments of human speech to generate the audio output. The system follows pronunciation, intonation, and expression rules to deliver the speech. TTS automation is typically less dynamic and natural compared to AI-based solutions, as it lacks the ability to learn and adapt from data.

AI-based text-to-speech involves using deep learning models, such as neural networks, to generate spoken audio. These models are trained on large datasets of human speech to learn the nuances of human language, including intonation, emotion, and natural speech patterns. As a result, AI-based TTS systems can produce more natural and expressive speech, resembling human voices.

While most eLearning software vendors rely on TTS automation, some AI-based text-to-speech software vendors, such as WellSaid Labs, NaturalReader, and ReadSpeaker, offer higher quality audio that sounds like human speech.

Understanding the differences between automation and AI is important when considering text-to-speech features for course development. While TTS automation is commonly used, AI-based text-to-speech offers a more natural and human-like experience.