Text-to-speech built around your language and use case

Create speech for the language, voice and experience you want to deliver. OctOpus brings speech generation and supported voice-model training into your data-science project, with paired audio and text, training code, curves and listening samples. Develop the voice, evaluate it and connect it to an application.

Choose the voice workflow you need

Generate speech with an available voice, use permitted reference audio through a supported voice-cloning service, or fine-tune a supported model with your dataset. Describe the language, speaker, tone and intended use. OctOpus uses those requirements to guide the available workflow and the data it needs.

Prepare aligned speech and text

Build the training dataset from recordings paired with the words actually spoken. The preparation workflow checks audio properties and missing or empty clips; your review adds the language and speaker context. Keep the recordings clear, the transcripts accurate and a separate set of sentences ready for listening evaluation.

Find a compatible base for your language

OctOpus checks a requested base against its language support, available training path, license and access requirements. You can name the model you want or ask for help choosing a compatible option. Keep the language, pronunciation needs and intended deployment in the brief so the selection follows the use case.

Listen, compare and evaluate

Review generated samples alongside the training curves and available validation measurements. Use held-out sentences with the names, numbers and expressions your audience will hear. Assess intelligibility, pronunciation, naturalness and speaker consistency. Listening review matters alongside numerical scores, and the recordings and voice must be authorized for the intended use.

Bring the voice into an application

Use supported generation and serving paths to turn new text into audio. Keep the selected voice and saved model artifact with the project configuration, then test synthesis on the intended deployment. A voice application can connect that output to a user flow such as reading information aloud or answering a request.

Example brief for a customer-service voice

“Prepare a voice in our target language for short service answers, with clear dates and amounts. Check compatible bases, review the data, train within my budget and show listening samples.” Use those samples to refine pronunciation and style, then test the phrases people will encounter in the application.

Key capabilities

• Language and use-case requirements guide voice selection.
• Aligned recordings and text for supported training workflows.
• Training curves, code and held-out listening samples.
• Speech generation connected to the product you are building.