Search Results for "whisper-cli.exe"
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Showing 74 open source projects for "whisper-cli.exe"
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Whisper
Robust Speech Recognition via Large-Scale Weak Supervision
OpenAI Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multitasking model that can perform multilingual speech recognition, speech translation, and language identification. A Transformer sequence-to-sequence model is trained on various speech processing tasks, including multilingual speech recognition, speech translation, spoken language identification, and voice activity detection. -
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whisper.cpp
Port of OpenAI's Whisper model in C/C++
whisper.cpp is a lightweight, C/C++ reimplementation of OpenAI’s Whisper automatic speech recognition (ASR) model—designed for efficient, standalone transcription without external dependencies. The entire high-level implementation of the model is contained in whisper.h and whisper.cpp. The rest of the code is part of the ggml machine learning library. The command downloads the base.en model converted to custom ggml format and runs the inference on all .wav samples in the folder samples. whisper.cpp supports integer quantization of the Whisper ggml models. ... -
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whisper-timestamped
Multilingual Automatic Speech Recognition with word-level timestamps
Multilingual Automatic Speech Recognition with word-level timestamps and confidence. Whisper is a set of multi-lingual, robust speech recognition models trained by OpenAI that achieve state-of-the-art results in many languages. Whisper models were trained to predict approximate timestamps on speech segments (most of the time with 1-second accuracy), but they cannot originally predict word timestamps. This repository proposes an implementation to predict word timestamps and provide a more accurate estimation of speech segments when transcribing with Whisper models. ... -
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WhisperLive
A nearly-live implementation of OpenAI's Whisper
WhisperLive is a “nearly live” implementation of OpenAI’s Whisper model focused on real-time transcription. It runs as a server–client system in which the server hosts a Whisper backend and clients stream audio to be transcribed with very low delay. The project supports multiple inference backends, including Faster-Whisper, NVIDIA TensorRT, and OpenVINO, allowing you to target GPUs and different CPU architectures efficiently. -
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Go OpenAI
OpenAI ChatGPT, GPT-3, GPT-4, DALL·E, Whisper API wrapper for Go
This library provides Go clients for OpenAI API. OpenAI ChatGPT, GPT-3, GPT-4, DALL·E, Whisper API wrapper for Go. -
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Voice-Pro
Comprehensive Gradio WebUI for audio processing
Voice-Pro is the best gradio WebUI for transcription, translation and text-to-speech. It can be easily installed with one click. Create a virtual environment using Miniconda, running completely separate from the Windows system (fully portable). Supports real-time transcription and translation, as well as batch mode. -
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WhisperSpeech
An Open Source text-to-speech system built by inverting Whisper
WhisperSpeech is an open-source text-to-speech system created by “inverting” OpenAI’s Whisper, reusing its strengths as a semantic audio model to generate speech instead of only transcribing it. The project aims to be for speech what Stable Diffusion is for images: powerful, hackable, and safe for commercial use, with code under Apache-2.0/MIT and models trained only on properly licensed data. Its architecture follows a token-based, multi-stage pipeline inspired by AudioLM and SPEAR-TTS: Whisper is used to produce semantic tokens, EnCodec compresses the waveform into acoustic tokens, and Vocos reconstructs high-fidelity audio from those tokens. ... -
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WhisperKit
On-device Speech Recognition for Apple Silicon
WhisperKit is a Swift package that integrates OpenAI's popular Whisper speech recognition model with Apple's CoreML framework for efficient, local inference on Apple devices. Whisper has pulled the future forward when fast, free and virtually error-free translation and transcription will be ubiquitous. It inspired numerous developers to improve and deploy it with minimal friction and maximum performance. -
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Meetily
Privacy first, AI meeting assistant with 4x faster Parakeet/Whisper
...It’s built for organizations that want meeting intelligence without sending recordings or transcripts to third-party cloud services, which helps address compliance and data sovereignty requirements. The app supports live transcription with local model options (including Whisper- and Parakeet-based workflows) and presents the transcript as the meeting happens, making it useful both for note-taking and accessibility. After or during the session, it can produce structured, AI-generated summaries, and it’s designed to be flexible about where that summarization comes from, supporting local providers as well as external endpoints when allowed by policy. -
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WhisperJAV
Uses Qwen3-ASR, local LLM, Whisper, TEN-VAD
...WhisperJAV introduces a specialized pipeline that separates text generation from timestamp alignment, allowing the system to generate transcripts and then align them with audio using forced alignment techniques. The framework supports several speech recognition models, including Qwen-based ASR systems and fine-tuned Whisper models trained on domain-specific dialogue. -
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Whisper-Studio
Another whisper wrapper, built fully in C++, with some neat features.
a native lightweight C++ application for OpenAI's Whisper, with a few new things like transcribing audio in real-time, identifying speakers, auto-paste transcriptions, and a few other things. Its not the prettiest app, I suck at design, but it gets the job done. -
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Handy STT
A free, open source, and extensible speech-to-text application
...Handy allows users to start transcription instantly using a configurable keyboard shortcut—press to record, release to transcribe—and automatically pastes the resulting text into any active text field. Its backend leverages OpenAI’s Whisper models for GPU-accelerated speech recognition and Parakeet V3 for efficient CPU-only transcription with automatic language detection. To further refine accuracy and responsiveness, Handy integrates Silero’s Voice Activity Detection (VAD) for silence filtering, ensuring only speech segments are processed. -
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Buzz
Transcribe and translate audio offline on your personal computer
Buzz transcribes and translates audio to text offline using OpenAI's Whisper. Import audio and video files into Buzz and export them as TXT, SRT, or VTT files. Buzz supports Whisper, Whisper.cpp, Faster Whisper, Whisper-compatible models from the Hugging Face repository, and the OpenAI Whisper API. Get linux versions from: - https://flathub.org/apps/io.github.chidiwilliams.Buzz - https://snapcraft.io/buzz Home page of Buzz https://github.com/chidiwilliams/buzz Note for Windows: App is not signed, you will get a warning when you install it. ... -
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HeartMuLa
A Family of Open Sourced Music Foundation Models
...The project also includes HeartCodec, a music codec optimized for high reconstruction fidelity, enabling efficient tokenization and reconstruction workflows that are critical for training and generation pipelines. For text extraction from audio, it provides HeartTranscriptor, a Whisper-based model tuned specifically for lyrics transcription, which helps bridge generated or recorded audio back into structured text. It also introduces HeartCLAP, which aligns audio and text into a shared embedding space. -
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AutoCut
Cut videos with a text editor
...This approach transforms video editing into a textual editing task, greatly lowering the barrier to editing for users who find traditional video editors complex or unintuitive. AutoCut supports multiple transcription backends, including Whisper and faster-whisper modes, allowing users to choose based on speed or accuracy needs. After editing the transcript text, the corresponding video clips are merged into the final output, and the tool also produces matching subtitle files. Its command-line interface can be integrated into scripts, making it suitable for automated workflows or batch processing. -
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Note67
A private, local meeting notes assistant
...Built with a cross-platform architecture using Rust (via Tauri) for backend logic and a TypeScript/React frontend, it prioritizes privacy by performing audio transcription locally with Whisper models and generating summaries with locally-hosted AI, eliminating the need to send sensitive meeting content to external servers. Users can record meetings directly from their microphone, view live transcriptions, filter by speaker, and export structured summaries, making it useful for professionals who need searchable, organized records of discussions. ... -
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Hyprnote
Local-first AI Notepad for Private Meetings
Hyprnote is an open-source, privacy-first AI notepad app designed for taking notes during meetings—transcribing audio (microphone and system) and generating context-rich summaries using on-device AI models like Whisper and HyprLLM, all without any data leaving your machine.(turn0search7, turn0search1). Listens to your meetings while you write. Crafts smart summaries based on your quick notes. Runs completely offline using open-source models like Whisper or HyprLLM. Use approved third-party APIs like Gemini, Claude, or Azure-hosted GPT. -
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ChatGPT Telegram Bot
A Telegram bot that integrates with OpenAI's official ChatGPT APIs
A Telegram bot that integrates with OpenAI's official ChatGPT, DALL·E and Whisper APIs to provide answers. Ready to use with minimal configuration required. -
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Speech Note
Speech Note Linux app. Note taking, reading and translating
...All processing is done locally, which means audio, text, and translations never leave the device, emphasizing strong privacy guarantees. The application supports multiple STT engines such as Coqui STT (DeepSpeech fork), Vosk, whisper.cpp, Faster Whisper, and april-asr, giving users flexibility in accuracy, speed, and hardware requirements. For text-to-speech, it can plug into a wide range of engines including espeak-ng, MBROLA, Piper, RHVoice, Coqui TTS, Mimic 3, WhisperSpeech, Kokoro, Parler-TTS, F5-TTS, and even classic S.A.M., making it highly customizable in terms of voices and languages. -
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Whisper-Transcriber-Tool
Desktop application that converts video files into accurate text
WhisperTranscriber is a free, powerful desktop application that converts video files into accurate text using OpenAI's Whisper AI model. Perfect for journalists, researchers, students, content creators, and anyone who needs reliable transcription. KEY FEATURES: - High-accuracy AI transcription with 99+ language support - Works completely offline - no internet required, total privacy - Supports all common video formats (mp4) - Batch processing for multiple files - Automatic language detection - Drag & drop interface - Export as SRT formats - No file size limits PORTABLE VERSION: - No installation needed - Run from USB or any folder - FFmpeg and AI models included - Lightweight and fast WHY CHOOSE WHISPERTRANSCRIBER: ✓ 100% free forever - no subscriptions or hidden costs ✓ Complete privacy - all processing happens on your computer ✓ No account or registration required ✓ Professional-grade accuracy ✓ Works offline -
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OpenAI .NET
The official .NET library for the OpenAI API
...Every synchronous method has an async counterpart, and the library offers convenient streaming primitives for chat completions so you can process tokens as they arrive. It supports tool/function calling, structured outputs via JSON schema, audio input/output, image generation, embeddings, Whisper transcription, and assistants with retrieval augmented generation. -
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Whisper Turbo
Cross-Platform, GPU Accelerated Whisper
Whisper Turbo is a fast, cross-platform Whisper implementation, designed to run entirely client-side in your browser/electron app. -
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Whisper Batch Transcriber
Unlimited, private and free Speech-To-Text program
## About: Automatically transcribe all of your voice recordings into clean, organized, neat text files. It's free, fully automated, unlimited, using state-of-the-art speech-to-text technology. Works 100% offline on your computer, privately and locally. ## Usecases: Convert speeches, podcasts, webinars, monologues, storytellings and other audio speech into a formatted .txt file. One sentence per new line. ## Notes: - Its 2GB in size and requires 2-6GB of GPU VRAM too. (basically... -
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Speech-AI-Forge
Speech-AI-Forge is a project developed around TTS generation model
...The system is designed to be deployed in several ways: you can try it online via hosted demos, spin it up in a one-click Colab environment, run it in Docker containers, or set it up locally with its environment preparation scripts. It is model-agnostic and advertises support for a variety of TTS and speech models such as ChatTTS, CosyVoice, Fish-Speech, FireredTTS and others, as well as Whisper-based ASR, giving you a flexible playground for experimenting with different speech stacks. The project also integrates with general-purpose LLMs (for example GPT- or LLaMA-style models), which can be used to pre-process text, manage conversations.
