RealtimeSTT

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RealtimeSTT is an Audio & Music tool that provides a robust, efficient, and low-latency speech-to-text library. It features advanced voice activity detection, wake word activation, and instant transcription for real-time applications.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is RealtimeSTT?

RealtimeSTT is an open-source, low-latency speech-to-text library designed for real-time applications, listening to microphone input and transcribing voice into text. It boasts advanced features like Voice Activity Detection, utilizing WebRTCVAD and SileroVAD for accurate speech detection, and Realtime Transcription powered by Faster_Whisper for instant, GPU-accelerated processing. The library also supports Wake Word Activation through Porcupine or OpenWakeWord, allowing activation upon detecting designated keywords. It's ideal for voice assistants and applications requiring fast and precise speech-to-text conversion, forming a powerful audio wrapper when combined with RealtimeTTS for text-to-voice capabilities. The project is community-driven, welcoming contributions for its continued development.

Best used for

Ideal for developers and engineers who need to build voice assistants, create applications with real-time speech-to-text capabilities, and enable wake word activation. Especially valuable for projects requiring low-latency and efficient transcription with advanced voice detection.

Common actions

transcribe speech in real-time

detect voice activity

activate with wake words

integrate speech recognition

workflowsdeepfakelow-code/no-codeopen-source"AI Agents"github copilotface swappingautomated workflowcollaboration

Capabilities

Key features

Low-latency speech-to-text
Voice Activity Detection
Realtime Transcription
Wake Word Activation
GPU-accelerated transcription
Microphone input processing
Audio chunk feeding

Target Audience

developersvoice assistant engineersai/ml engineersrobotics engineers

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What are the core technologies used by RealtimeSTT for speech processing?

RealtimeSTT leverages WebRTCVAD and SileroVAD for Voice Activity Detection, Faster_Whisper for instant speech-to-text transcription, and Porcupine or OpenWakeWord for wake word detection. These components are considered industry standards for high-performance applications.

Does RealtimeSTT support GPU acceleration for transcription?

Yes, RealtimeSTT supports GPU acceleration, particularly with CUDA-enabled NVIDIA GPUs. Users can upgrade their PyTorch installation to utilize CUDA 11.8 or 12.X for significantly enhanced performance, especially with larger speech-to-text models.

Can RealtimeSTT be used without a microphone?

Yes, RealtimeSTT can be used without a microphone. By setting the `use_microphone` parameter to `False`, users can feed raw PCM audio chunks (16-bit mono, 16000 samplerate) directly to the recorder for transcription.

What is the project status of RealtimeSTT?

RealtimeSTT is currently community-driven. The original maintainer is no longer actively implementing new features or providing user support due to time constraints but will continue to review and merge high-quality pull requests from the community.

How does RealtimeSTT handle wake word activation?

RealtimeSTT allows users to specify a comma-separated list of desired activation keywords using the `wake_words` parameter. It supports a predefined list of wake words like "jarvis," "alexa," and "hey google," activating transcription upon detection.

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