Tagged "speech-to-text"
15 articles tagged speech-to-text, 18 March 2026 to 9 August 2026. Newest first.
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ShoutFlow Launches Pay-Once, On-Device AI Dictation App for the Mac
ShoutFlow releases a consumer-focused on-device AI application that performs speech-to-text dictation locally on macOS with a one-time purchase model.
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Voice Notes Shouldn't Cross the Ocean – Keep Your Thoughts Private
An argument for local processing of voice notes instead of cloud transmission. This highlights the privacy and latency advantages of on-device inference for audio workloads.
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Wisprkey – 100% Free and Local Voice Typing for Mac
A free, fully local voice-to-text application for macOS that processes speech entirely on-device without cloud dependency.
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Mozilla AI Releases Llamafile 0.10.4 With New Transcribefile Built On Transcribe.cpp
Mozilla has updated Llamafile to version 0.10.4, introducing Transcribefile, a new tool built on Transcribe.cpp for local audio transcription without external dependencies. This expansion of the Llamafile ecosystem enables developers to run speech-to-text inference entirely on-device.
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Show HN: Turn Meeting Recordings into Searchable Transcripts. All Local
A new tool enables local transcription and search of meeting recordings without sending data to cloud services. This demonstrates practical on-device inference for speech-to-text workflows.
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Transcribe.cpp – ggml speech-to-text inference engine
A new GGML-based speech-to-text inference engine enabling local, on-device transcription without cloud dependencies. This tool extends the ggml ecosystem to multimodal local inference capabilities.
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Privatewhisper.ai: Private AI Voice Dictation Without Typing
Privatewhisper.ai enables on-device speech-to-text processing using local models, offering privacy-preserving voice dictation without sending audio to cloud servers.
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PipeVoice: The Free Local Alternative to Whisper Flow
PipeVoice offers a free, open-source alternative for local speech-to-text processing without reliance on cloud services. This tool enables on-device audio transcription, making it ideal for privacy-conscious deployments and edge inference scenarios.
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Audio Processing Support Lands in llama.cpp with Gemma-4
llama.cpp now supports speech-to-text functionality with Gemma-4 E2A and E4A models, enabling local multimodal inference on consumer hardware. This expansion brings audio capabilities to the most widely-used local LLM inference engine.
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Ask HN: Local-First Meetings Recorder and Transcriber
A Hacker News discussion exploring open-source, on-device solutions for recording and transcribing meetings without cloud dependency, highlighting practical applications of local speech and language models.
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Google AI Edge Gallery Showcases Offline Inference with Gemma 4
Google has launched the AI Edge Gallery application demonstrating practical use cases for offline inference with Gemma 4 on iOS and Android, including offline dictation and on-device AI features without internet connectivity.
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Google's Gemma 4 Brings Powerful On-Device AI to Android and iOS
Google has released Gemma 4, optimized for local deployment on smartphones and laptops, making it easier than ever to run capable models directly on-device without cloud dependencies. The model powers new applications like Google's AI Edge Eloquent dictation app, demonstrating practical privacy-preserving inference on mobile platforms.
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A Journey to a Reliable and Enjoyable Locally Hosted Voice Assistant
An in-depth guide documenting the development and deployment of a fully local voice assistant, covering the complete stack from speech recognition to language understanding and synthesis without cloud dependencies.
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Careless Whisper – Personal Local Speech to Text
A new open-source tool enabling local speech-to-text processing without cloud dependencies, bringing private voice input capabilities to on-device LLM applications.
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Browser-Based Transcription Tools
Browser-based transcription solutions leverage local inference to enable audio processing entirely within the user's device, eliminating cloud dependency for speech-to-text tasks. This trend reflects growing adoption of WebAssembly and on-device AI models for privacy-preserving audio applications.