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GRAPHLOGIC
TEXT-TO-SPEECH API

Unleash Superior Speech-to-Text Capabilities with Cutting-Edge Features: Customized speech models, Speech synthesis markup language (SSML) and many more.

Speed: 50 ms latency

Demo Try it now
Demo Try it now
Speech recognition models
Graphlogic TTS
Convert text into natural-sounding speech with high efficiency and accuracy. It is optimized for low latency and high performance, making it suitable for handling large volumes of requests quickly.
Custom - Bring Your Own Model
Bring your custom models to connect to or tailor GL TTS to better fit unique vocabulary of your customers.
Features
Customised speech models
Generate voice to communicate unique brand personas of your customers
Data depersonalisation
Depersonalise data on your side to ensure data protection
Multiple languages
Multilingual support to serve your customers worldwide
Speech synthesis markup language (SSML)
Enable higher customisation in your audio response by providing details on pauses and voice pitch, and audio formatting for acronyms, dates, times, abbreviations, or text that should be censored. Enterprise-grade scalability
Enterprise-grade scalability
Handle significant workload increases while maintaining performance.
How to launch?
STEP 1
Deliver a dataset
STEP 2
A model is to be trained
STEP 3
A model is to be deployed
STEP 4
Monitor and improve the accuracy

Use Cases

  • Creating brand voices
  • Creating voice ads or for podcasts
  • Generating human-like voice for digital avatars
  • Indoor navigation for hospitals
  • Indoor navigation for museums

Frequently Asked Questions

How many languages are supported?

For now we support English, German, Spanish, Russian, and Thai

How long will it take to develop a new language?

A 1000-hour heterogeneous speech training dataset is required to develop a new language. Exact terms will be subject to the quality of this dataset and whether a model for this language already exists or not.

What is SSML?

SSML (Speech Synthesis Markup Language) is a markup language made for speech synthesis applications. It is used to apply tweaks and adjustments to synthetic voices, e.g., to make the voice higher on a specific part of speech.

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