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Description

Higgs Audio / Avatar represents a versatile suite of foundational audio and avatar technologies that create realistic speech, comprehend tone, emotion, and intent, and provide a visual element to voice interactions. These models encompass capabilities such as text-to-speech, speech-to-text, avatar creation, and smart voice casting, which intelligently chooses a suitable voice based on context, sentiment, and content. Designed for practical use in production environments, Higgs merges expressive generation with strong speech comprehension and adaptable deployment suited for situations where quality, latency, and dependability are crucial. With high-precision multilingual speech recognition across primary languages, the technology also features voice cloning that captures a speaker’s unique tone from brief samples, ensuring brand voice consistency in various interactions. Additionally, sentiment analysis interprets emotional cues in speech, facilitating improved routing, enhanced analytics, and more context-aware agent responses, ultimately leading to a more engaging user experience. This comprehensive approach not only elevates communication but also empowers businesses to connect more effectively with their audiences.

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
Deep Infra
EigenCloud
Microsoft Foundry

Integrations

Boson AI
Deep Infra
EigenCloud
Microsoft Foundry

Pricing Details

No price information available.
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

www.boson.ai/higgs-audio

Vendor Details

Company Name

Meta

Founded

2004

Country

United States

Website

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

Product Features

Product Features

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