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The WebRTC.ventures Blog.

HomecategoryThe WebRTC.ventures BlogPage 14
March 26, 2025
Dilermando SikoraComments Off on Real-Time Speech Transcription on Android with SpeechRecognizer

Real-Time Speech Transcription on Android with SpeechRecognizer

Voice-to-text technology has advanced significantly, enabling real-time transcription for various applications. From enhancing workplace productivity to supporting individuals with disabilities, speech-to-text solutions have become integral across numerous sectors. Professionals in fields like journalism, legal services, education, and healthcare, to name a few, are leveraging real-time transcription to

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March 14, 2025
Lucas SchnöllerComments Off on Voice + Action: The Convergence of WebRTC, Conversational AI, and Agentic Systems

Voice + Action: The Convergence of WebRTC, Conversational AI, and Agentic Systems

The integration of conversational AI and agentic systems into WebRTC applications has evolved from a novel concept to an essential component in creating truly intelligent communication systems. The convergence of real-time communication, large language models (LLMs), and agentic AI systems has unlocked new opportunities for voice-based interfaces

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February 21, 2025
Hector ZelayaComments Off on Implementing Pre-Call Tests for Better Real-Time Communication Experiences

Implementing Pre-Call Tests for Better Real-Time Communication Experiences

Real-time video calls have become the backbone of how we work, learn, and connect. And when users connect, they expect seamless, high-quality communication. Yet many factors can affect call quality – from internet connectivity to device settings to network configurations. While these issues often originate outside the

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February 11, 2025
Alberto GonzalezComments Off on When GPU Matters in WebRTC: Accelerating AI, Video Streaming, and Real-Time Communication

When GPU Matters in WebRTC: Accelerating AI, Video Streaming, and Real-Time Communication

Graphics Processing Units (GPUs) were originally designed to accelerate gaming, enabling complex graphics computations to run in parallel. Unlike Central Processing Units (CPUs), which excel at executing a few instructions at a time with high precision, GPUs are built for massive parallelism—handling thousands of operations simultaneously.  This

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