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Description

Higgs Realtime is an advanced model and API that delivers production-ready, real-time speech-to-speech capabilities, designed to facilitate seamless and natural conversations. This comprehensive, instruction-optimized, audio-centric model is proficient in processing audio, text, or both, generating high-quality responses, and can also serve as a text-based language model when only text input is provided. Tailored for live voice interactions, it adeptly follows dialogues, manages interruptions, and adjusts to evolving requests even mid-conversation, while successfully navigating complex multi-step workflows. The model is specifically developed to exhibit voice-agent traits such as smooth turn-taking, conversational rhythm, tone modulation, introductory phrases for spoken tools, tracking of multi-turn states, and effectively responding to dynamic instructions. Enhanced semantic turn detection distinguishes between finished exchanges and brief pauses, while its multilingual and code-switching capabilities enable comprehension of over 100 languages without requiring specific setups for each language. In this way, Higgs Realtime not only enhances the user experience but also promotes greater accessibility in diverse communication scenarios.

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

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Boson AI

Integrations

Boson AI

Pricing Details

$0.0023 per minute
Free Trial
Free Version

Pricing Details

No price information available.
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

Boson AI

Founded

2023

Country

United States

Website

staging.boson.ai/blog/higgs-realtime

Vendor Details

Company Name

Meta

Founded

2004

Country

United States

Website

research.meta.ai/blog/introducing-muse-voice-transcribe

Product Features

Product Features

Alternatives

Alternatives

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