realtime speech-to-text
Python real-time speech-to-text library with voice activity detection, wake word activation, and streaming transcription.
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
Choose when you need training/finetuning or an all-in-one ASR/VAD/diarization pipeline; it is much heavier than RealtimeSTT.
Open-source speech recognition toolkit for training, inference, streaming ASR, VAD, punctuation, speaker diarization pipelines, and OpenAI-compatible/MCP serving.
Choose for a research-grade speech framework with many models and training support; it is far heavier than a lightweight realtime library.
A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
Choose for Swift/CoreML Apple apps where a Python library cannot be embedded; it is platform-specific to Apple.
Frontier CoreML audio models in your apps — text-to-speech, speech-to-text, voice activity detection, and speaker diarization. In Swift, powered by SOTA open source.
Choose for Apple Silicon apps using MLX/CoreML; it is Swift-only and Apple-only.
AI speech toolkit for Apple Silicon — ASR, TTS, speech-to-speech, VAD, and diarization powered by MLX and CoreML
Choose when you want Whisper-specific streaming with diarization/translation; it is an alternative library but not API-compatible.
Real-time, local speech-to-text with streaming ASR, speaker diarization, translation, and OpenAI/Deepgram-compatible APIs.
Choose for extremely low-latency C++ voice agents with TTS/intent; it is a different language and not a Python library.
Very low latency speech to text, intent recognition, and text to speech, for building voice agents and interfaces
Choose for C++/ggml-based STT inference across many model families; it is lower-level than RealtimeSTT.
ggml speech-to-text inference for 16+ model families
Choose for a pure C++ audio inference engine with STT/TTS/VAD; it has no Python dependency.
An all-in-one, pure C++ inference engine for audio models, powered by ggml. Supports TTS, STT, VAD, voice conversion, music generation, and more, with highly optimized performance. No Python dependency.
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
Choose only when you need a simpler, Whisper-only streaming implementation; it lacks the multi-engine support and wake word of RealtimeSTT.
Whisper realtime streaming for long speech-to-text transcription and translation
Does the same job, but ships as an app. Useful to a person, not swappable into a codebase.
It is a macOS app for private transcription, not a library you can embed.
100% private on-device voice models for speech-to-text and meeting transcription on macOS
It is an end-user voice app suite for cloning/dubbing/transcription, not an embeddable library.
VoiceStudio is the open-source, fully-local ElevenLabs alternative — voice cloning, voice design, video dubbing, dictation, transcription & audiobook creation in 646 languages.
It is a GUI batch transcription tool, not a library.
✨ AsrTools: Smart Voice-to-Text Tool | Efficient Batch Processing | User-Friendly Interface | No GPU Required | Supports SRT/TXT Output | Turn your audio into accurate text in an instant!
It is a web service wrapper around Whisper, not a library to embed.
OpenAI Whisper ASR Webservice API
It is an open-source dictation app, not a Python STT library.
🎙️ AI Dictation App - Open Source and Local-first ⚡ Type 3x faster, no keyboard needed. 🆓 Powered by open source models, works offline, fast and accurate.
These projects were analysed and named RealtimeSTT among their alternatives. The relationship is not symmetric — how RealtimeSTT rates them is a separate judgement, made when RealtimeSTT is analysed in its own right.
calls RealtimeSTT “use it for low-latency streaming STT with VAD/wake-word, a slim library around Whisper rather than a unified long-form model”
Open-Source Frontier Voice AI
calls RealtimeSTT “choose for low-latency STT with VAD and wake-word support.”
Speech recognition module for Python, supporting several engines and APIs, online and offline.
calls RealtimeSTT “choose for a drop-in real-time STT library with VAD and wake word, based on Whisper.”
Open-source speech recognition toolkit for training, inference, streaming ASR, VAD, punctuation, speaker diarization pipelines, and OpenAI-compatible/MCP serving.
calls RealtimeSTT “choose when you want a ready Python realtime STT library with VAD/wake-word handling instead of building a model pipeline.”
A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)