Related Products
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About
Deploy accurate speech recognition at scale while continuously improving model performance by labeling data and training from a single console. We deliver state-of-the-art speech recognition and understanding at scale. We do it by providing cutting-edge model training and data-labeling alongside flexible deployment options. Our platform recognizes multiple languages, accents, and words, dynamically tuning to the needs of your business with every training session. The fastest, most accurate, most reliable, most scalable speech transcription, with understanding — rebuilt just for enterprise. We’ve reinvented ASR with 100% deep learning that allows companies to continuously improve accuracy. Stop waiting for the big tech players to improve their software and forcing your developers to manually boost accuracy with keywords in every API call. Start training your speech model and reaping the benefits in weeks, not months or years.
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About
Muse Voice Transcribe is Meta’s first real-time audio perception model, delivering streaming automatic speech recognition (ASR), diarization, and endpointing in real time. An autoregressive multimodal model from the Muse Spark family, it processes audio in 80 ms chunks and decides dynamically whether to continue listening or emit text. Its adaptive delay changes the amount of audio context used for each word based on difficulty, balancing transcription accuracy with latency. The model is trained on more than 70 languages, with 25 extensively verified at launch, and natively supports arbitrary code-switching both within and between sentences. Language, keyword, and context biasing can further improve recognition accuracy for specific names, places, contacts, or terminology. Streaming diarization identifies speaker changes and distinguishes more than 20 speakers, while endpointing detects when speech begins and when a user finishes speaking.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Companies looking for Speech to Text (STT) API for real-time and batch transcriptions, on premise or in the cloud.
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Audience
Developers and AI researchers seeking to build real-time voice applications that transcribe multilingual speech, distinguish speakers, and detect conversational turns
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
$0
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationDeepgram
Founded: 2015
United States
deepgram.com
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Company InformationMeta
Founded: 2004
United States
research.meta.ai/blog/introducing-muse-voice-transcribe
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Categories |
Categories |
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Speech Recognition Features
Audio Capture
Automatic Form Fill
Automatic Transcription
Call Analysis
Concatenated Speech
Continuous Speech
Customizable Macros
Multi-Languages
Specialty Vocabularies
Speech-to-Text Analysis
Variable Frequency
Voice Recognition
Transcription Features
AI / Machine Learning
Annotations
Audio/Video File Upload
Automatic Transcription
Collaboration Tools
File Sharing
For Manual Transcription
Full Text Search
Multi-Language Support
Natural Language Processing (NLP)
Playback Controls
Speech Recognition
Subtitles
Text Editor
Timecoding
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Integrations
Amazon Web Services (AWS)
Axis LMS
Deepgram Saga
Docker
Dograh
Genesys Cloud CX
Hunch
Kubernetes
Line 21
LiteLLM
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Integrations
Amazon Web Services (AWS)
Axis LMS
Deepgram Saga
Docker
Dograh
Genesys Cloud CX
Hunch
Kubernetes
Line 21
LiteLLM
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