When you choose a voice for your text-to-speech project, you will likely encounter the terms "standard voice" and "neural voice". Although both types of voices convert text to speech, the underlying technology and the quality of the result are very different. Understanding this difference is essential to choosing the best option for your project.
Standard (or concatenative) voices
Standard voices, also known as concatenative voices, are the first-generation text-to-speech technology. They work by recording thousands of small speech segments (diphones, i.e., transitions from one sound to another) from a voice actor. Then, when you submit a text, the TTS engine searches for the corresponding segments in its database and assembles them to form words and sentences.
Advantages:
- Less computationally intensive than neural voices.
- Can be very intelligible and clear for simple applications.
Disadvantages:
- Often sound robotic and monotonous.
- Lack fluidity and naturalness in the transitions between words.
- The prosody (rhythm, intonation) is often flat and artificial.
Neural voices
Neural voices represent a major breakthrough in text-to-speech technology. They use deep learning models to generate speech from scratch. Instead of assembling pre-recorded segments, these models learn the complex relationships between text and speech by analyzing huge amounts of audio data. They then generate the audio waveform sample by sample, which allows them to capture the subtleties of human speech.
Advantages:
- Exceptional naturalness and fluidity, very close to the human voice.
- Realistic prosody, with variations in intonation and rhythm.
- Ability to produce more expressive and emotional voices.
Disadvantages:
- Require significant computing power for training and generation.
- Can sometimes produce sound artifacts or unexpected pronunciations.
When to choose which voice?
For most modern applications, neural voices are the preferred choice. Their superior quality offers a much better user experience, whether for audiobooks, voice assistants, explainer videos, or accessibility applications. Standard voices can still be useful in very specific contexts where computing resources are extremely limited, such as some embedded systems.
Conclusion
The transition from standard voices to neural voices has been a true revolution in the world of text-to-speech. At Free TTS, we are committed to offering you the highest quality neural voices so that your projects sound professional, natural, and engaging. The next time you choose a voice, you will know exactly what is behind the terms "standard" and "neural", and you can make an informed choice.