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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.
Description
Spoken is an innovative API designed to convert any publicly available podcast into a polished Markdown transcript that includes the actual names of the speakers instead of generic labels like "Speaker 1." With a single API request, users can obtain named, timestamped text that is compatible with LLMs, RAG pipelines, summarizers, and search functionalities. Instead of needing to handle speech-to-text processing and speaker identification on your own, Spoken directly provides transcripts of published podcasts while also identifying speaker names, typically at a cost that is 5-10 times lower for these shows. Users can search by entering text or by pasting a Spotify or YouTube URL, which enhances accessibility. Additionally, the service operates on a pay-per-use basis without requiring a subscription; users will not be billed for unsuccessful calls, and any repeat fetches are provided free of charge. The API is designed to be agent-native, and it comes equipped with an Agent Skill, along with resources like agents.md, llms.txt, and an OpenAPI specification. To help users get started, a free demo key is available, and paid credits can be purchased starting at just $15, making it an attractive option for anyone looking to utilize podcast transcripts efficiently. With its user-friendly features and cost-effective model, Spoken is paving the way for easier access to podcast content.
API Access
Has API
API Access
Has API
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$15
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Meta
Founded
2004
Country
United States
Website
research.meta.ai/blog/introducing-muse-voice-transcribe
Vendor Details
Company Name
Spoken
Founded
2026
Country
Netherlands
Website
spoken.md