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Average Ratings 0 Ratings
Description
Ink 2 represents Cartesia's most advanced and precise streaming speech-to-text model, designed specifically for production voice agents, boasting the lowest word error rate and superior turn detection of any available streaming STT. This model excels in accurately transcribing structured data types like phone numbers, dates, and email addresses on the first attempt, while intuitively recognizing when a speaker begins and ends their speech, eliminating the need for a separate voice activity detection mechanism. Integrated turn detection allows voice agents to respond to events seamlessly, rather than sifting through raw transcript segments. Ink 2 generates a comprehensive array of turn events, providing agents with definitive cues regarding when to listen, interrupt, contemplate, prepare to respond, retract an untimely reply, or engage in conversation. Additionally, the transcript retains a cumulative nature within each turn, ensuring that every update presents the complete text transcribed up to that point rather than just the incremental changes, and the emitted text is considered final the moment it is sent. This innovative design enhances the interaction quality between voice agents and users, making conversations smoother and more effective.
Description
Muse Voice Transcribe represents Meta’s inaugural venture into real-time audio perception, providing instantaneous automatic speech recognition (ASR), speaker diarization, and endpointing capabilities. This autoregressive multimodal model, part of the Muse Spark series, analyzes audio segments of 80 milliseconds and makes real-time decisions on whether to keep listening or to convert the spoken words into text. The adaptive delay mechanism allows it to adjust the audio context utilized for each word according to the complexity of the speech, thus optimizing the balance between transcription precision and response time. With training encompassing over 70 languages, 25 of which were rigorously validated at the time of its release, the model also seamlessly accommodates arbitrary code-switching, allowing transitions within and across sentences. Furthermore, language, keyword, and contextual biasing features enhance the recognition capabilities for specific names, locations, contacts, or specialized terms. The streaming diarization functionality enables the model to recognize shifts in speakers and can differentiate between more than 20 individual voices. Additionally, the endpointing feature is adept at identifying the commencement of speech and knowing when a user has completed their statement, ensuring a fluid interaction experience. Overall, Muse Voice Transcribe stands out as a cutting-edge tool in the realm of speech recognition technology, merging advanced features with user-friendly application.
API Access
Has API
Yes
API Access
Has API
Yes
Integrations
MachinesFluent
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Cartesia
Founded
2023
Country
United States
Website
docs.cartesia.ai/build-with-cartesia/stt/latest
Vendor Details
Company Name
Meta
Founded
2004
Country
United States
Website
research.meta.ai/blog/introducing-muse-voice-transcribe