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What is Inworld TTS?

Inworld TTS emerges as a state-of-the-art text-to-speech technology that delivers remarkably lifelike and context-sensitive speech synthesis, complete with sophisticated voice-cloning capabilities, all at a highly competitive price point. Its flagship model, TTS-1, is designed for real-time applications, featuring low-latency streaming that provides the initial audio output in approximately 200 milliseconds and encompasses a broad spectrum of languages, including English, Spanish, French, Korean, and Chinese, among others. Developers can choose between instant zero-shot voice cloning, which requires merely 5 to 15 seconds of audio input, or more comprehensive fine-tuned cloning, which allows for the incorporation of voice-tags to express emotion, style, and non-verbal signals, while also facilitating seamless language transitions without compromising the distinct voice identity. Additionally, for users desiring enhanced expressiveness and multilingual support, the TTS-1-Max model is currently available in preview, showcasing improved functionalities. The platform supports multiple access methods, such as APIs and portal options, and can function in streaming or batch processing modes, making it adaptable for a wide array of uses, including interactive voice assistants, gaming avatars, and custom audio branding projects. With its innovative features and flexibility, Inworld TTS is set to transform the landscape of synthetic voice interactions and enhance user experiences across various domains. As users continue to explore the possibilities, the technology promises to pave the way for more engaging and personalized audio experiences.

What is Griffin?

Griffin is recognized as Tavus’s first Human Interaction Model, an advanced full-duplex video-to-video system designed to interpret and generate real-time, face-to-face human engagements. Unlike traditional conversational systems that address speech recognition, language modeling, and speech synthesis in a step-by-step process, Griffin functions by constantly processing audio and video inputs, making prompt decisions for responses, and simultaneously providing expressive verbal and visual feedback. It pays close attention not only to the verbal content but also to the nuances of tone, eye contact, facial expressions, gestures, pauses, interruptions, and the overall visual context. This model demonstrates functionality such as backchanneling, yielding or taking conversational turns, effectively managing interruptions, staying engaged during silences, and modifying its emotional tone and nonverbal signals as the conversation progresses. Additionally, Griffin can create a rich visual scene based on a reference image, encompassing aspects like facial features, body movements, hand gestures, chair positioning, shadows, and background details, which enables it to offer a more immersive experience beyond merely presenting a talking head. The integration of these capabilities significantly enriches the quality and realism of human-like interactions, making conversations feel more genuine and engaging.

Media

Media

Integrations Supported

Claude
Fireworks AI
Google AI Overviews
Groq
Inworld
LiveKit
Mistral AI
OpenAI
Tenstorrent DevCloud
Vapi AI
gpt-oss-20b

Integrations Supported

Tavus

API Availability

Has API

API Availability

Has API

Pricing Information

$0.005 per minute

Pricing Information

$22 per month
Free Version

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

Inworld

Date Founded

2021

Company Location

United States

Company Website

inworld.ai/tts

Company Facts

Organization Name

Tavus

Date Founded

2020

Company Location

United States

Company Website

www.tavus.io/griffin

Categories and Features

AI Voice Models

Not specified

Text to Speech

Not specified

Categories and Features

AI Models

Not specified

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