Text-to-Speech (TTS)

Text-to-speech (TTS) is AI technology that converts written text into spoken audio. Modern TTS systems produce speech that is increasingly indistinguishable from human voices, with natural intonation, emotion, and pacing.

How modern TTS works

Early TTS systems sounded robotic because they concatenated pre-recorded sound fragments. Modern neural TTS uses deep learning to generate speech end-to-end:

1. Text analysis: The input text is processed to understand pronunciation, emphasis, and phrasing. Abbreviations, numbers, and special characters are expanded.
2. Acoustic modelling: A neural network converts the processed text into a spectrogram — a representation of the audio's frequency content over time.
3. Waveform synthesis: A vocoder converts the spectrogram into actual audio waveform.

Some newer models combine these steps into a single end-to-end network.

Key TTS providers

• ElevenLabs: Highest quality, with voice cloning and emotional expression.
• OpenAI TTS: Integrated with the GPT ecosystem, multiple voices available.
• Google Cloud TTS: Wide language support, WaveNet voices.
• Amazon Polly: Integrated with AWS, cost-effective for high volume.
• Microsoft Azure Speech: Strong enterprise features and customisation.
• Coqui / XTTS: Open-source options for self-hosted deployment.

Voice cloning

Modern TTS platforms can clone a voice from just a few minutes of sample audio. This enables:

• Creating consistent brand voices for customer-facing audio.
• Producing audio content in a specific person's voice (with consent).
• Generating multi-voice audio for different characters.

Business applications

• Voice interfaces: Adding spoken responses to chatbots and virtual assistants.
• Content accessibility: Converting articles, documents, and courses into audio.
• E-learning: Narrating training materials without hiring voice actors for every update.
• Customer service: Natural-sounding IVR systems and automated phone responses.
• Audiobook production: Generating audiobook narration at a fraction of traditional cost.
• Localisation: Creating spoken content in multiple languages from a single text source.

Quality and ethics

• Naturalness: Modern TTS is remarkably natural but can still sound slightly off on complex sentences, emotional passages, or uncommon words.
• Consent: Voice cloning raises serious consent issues. Using someone's voice without permission is ethically problematic and increasingly regulated.
• Disclosure: Best practice is to disclose when audio is AI-generated.
• Deepfakes: TTS technology can be misused for impersonation and fraud.