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What is Cartesia Sonic-3.5?

Sonic 3.5 is Cartesia's pinnacle of text-to-speech innovation, designed for fluid voice synthesis with a remarkable latency of less than 90 milliseconds and the capability to communicate in 42 languages. This advanced model excels at following transcripts accurately, vocalizing confirmation codes, and interpreting heteronyms seamlessly without requiring any preprocessing, all while embodying the expressive qualities necessary for authentic conversations. Its objective is to deliver speech that rivals native quality across a wide range of languages, prioritizing audio clarity in every output and eliminating any need for post-production adjustments. Sonic 3.5 stands out by providing high-fidelity audio, making it particularly suitable for production settings where quality, speed, and dependability are crucial. The model features a captivating conversational style with effective pacing and a genuine emotional spectrum, which is specifically tuned for various support and agent transcripts. Additionally, it articulates alphanumeric sequences—like order numbers, phone numbers, IDs, and email addresses—naturally in all supported languages, while its context-aware English pronunciation guarantees that words such as "read," "bass," and "bow" are articulated correctly according to their textual context. This remarkable sophistication in voice generation significantly enriches the user experience, positioning Sonic 3.5 as a frontrunner in the realm of text-to-speech technology. With its continuous enhancements, Sonic 3.5 promises to reshape how we interact with digital voices in the future.

What is Cartesia Ink 2?

Ink 2 is Cartesia’s latest and most sophisticated streaming speech-to-text model, tailored specifically for production voice agents, and it features the industry's lowest word error rate alongside exceptional turn detection capabilities. This model shines in its ability to accurately transcribe structured data such as phone numbers, dates, and email addresses on the initial attempt, while also instinctively identifying when a speaker starts and stops talking, thus negating the requirement for a separate voice activity detection system. The built-in turn detection facilitates seamless responses from voice agents to various events, eliminating the hassle of analyzing raw transcript fragments. Ink 2 produces a detailed array of turn events that provide agents with clear indicators on when to listen, interrupt, reflect, prepare to respond, retract an inappropriate response, or engage in dialogue. Furthermore, the transcript maintains a cumulative format throughout each turn, ensuring that every update reflects the entire text transcribed up to that moment rather than merely highlighting incremental changes, with the emitted text being deemed final immediately upon transmission. This cutting-edge design significantly elevates the quality of interactions between voice agents and users, fostering smoother and more effective conversations while enhancing overall user experience. Ultimately, Ink 2 represents a significant leap forward in the realm of speech recognition technology.

Media

Media

Integrations Supported

Integrations Supported

MachinesFluent

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Cartesia

Date Founded

2023

Company Location

United States

Company Website

docs.cartesia.ai/build-with-cartesia/tts-models/latest

Company Facts

Organization Name

Cartesia

Date Founded

2023

Company Location

United States

Company Website

docs.cartesia.ai/build-with-cartesia/stt/latest

Categories and Features

AI Models

Not specified

AI Voice Models

Not specified

Categories and Features

AI Models

Not specified

AI Voice Models

Not specified

Speech to Text

Not specified

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