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Description
MAI-Transcribe-2-Streaming represents a cutting-edge solution in low-latency streaming transcription, specifically designed for real-time speech applications and capable of providing transcripts in 60 different languages with the added feature of automatic, continuous language detection. Instead of waiting for the completion of speech, this model generates initial partial transcripts in just over 100 milliseconds after audio input, allowing it to refine and enhance these transcripts as additional context becomes available, ultimately stabilizing the text quickly. This functionality enables voice applications to start analyzing information, utilizing tools, or showing live transcripts even while the speaker is still talking. According to Microsoft, this model has achieved the top ranking for both final and partial transcript accuracy on Artificial Analysis. To further enhance the user experience, MAI-Voice-2.1 offers a multilingual text-to-speech capability that spans 23 languages and 26 locales, enabling a single voice to seamlessly transition between languages while preserving the original speaker's identity and adopting local accents. This integration not only improves the usability of speech applications but also makes them more accessible to a diverse audience.
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
No
API Access
Has API
Yes
Integrations
No details available.
Integrations
No details available.
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
Microsoft AI
Founded
2024
Country
United States
Website
microsoft.ai/news/our-first-streaming-transcription-model/
Vendor Details
Company Name
Meta
Founded
2004
Country
United States
Website
research.meta.ai/blog/introducing-muse-voice-transcribe