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Description
In various GVC applications, the initial phase involves recognizing emotions: the user vocalizes for several seconds, and the GVC Emotion Recognition algorithm evaluates numerous acoustic characteristics of their voice to derive an understanding of their emotional condition. The outcomes from our emotion recognition system can then be utilized by other algorithms to select suitable responses for the user. At GVC, our main focus is on types of feedback that enhance the user's performance and overall quality of life. This includes analyzing signals from the user's voice, heart, lungs, and other bodily organs. The GVC concept has been put into practice in a range of demonstration applications. These applications utilize a collection of proprietary algorithms that assess various aspects of the user's speech, including the GVC Emotion Recognition and GVC Voice Disorder Detection algorithms, ultimately aiming to create a more responsive and supportive user experience. By integrating advanced technology, we strive to foster a deeper connection between the user's emotional state and the feedback provided.
Description
Inworld Realtime STT is a streaming API for speech-to-text that captures more than just spoken words. This innovative tool merges low-latency speech recognition with voice profiling capabilities, allowing it to analyze emotions, vocal style, accent, age, and pitch from raw audio inputs, which enhances the responsiveness and expressiveness of downstream LLMs and TTS systems. Developers have the flexibility to stream audio in real time, transcribe entire files, or gather voice profile signals via a single, comprehensive API. The system features real-time bidirectional streaming over WebSocket, synchronous transcription for complete audio files, and offers voice profile signals for each streaming segment, all while supporting multiple providers through one model ID. Each audio segment provides a dynamic profile of the speaker, complete with confidence scores, equipping LLMs with structured context that indicates the emotional state of the user, such as whether they sound sad, frustrated, soft-spoken, high-pitched, or calm. This capability allows for a more nuanced interaction, enriching the user experience by adapting responses to the speaker’s emotional tone and vocal characteristics.
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
Free
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
Good Vibrations Company
Founded
2011
Country
Netherlands
Website
good-vibrations.nl/
Vendor Details
Company Name
Inworld
Founded
2021
Country
United States
Website
inworld.ai/speech-to-text
Product Features
Emotion Recognition
Facial Emotions
Facial Expression Analysis
Machine Learning
Photo Emotions
Speech Emotions
Video Emotions
Written Text Emotions