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Software like OpenAI Whisper
What else does this job. Matched on what each project does, not on who links to whom.
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- Whisper Largehuggingface.coWhisper Large v3 is an open-source automatic speech recognition model developed by OpenAI. It transcribes spoken audio into text, supports multiple languages, and is robust to noise, making it suitable for developers and researchers building speech-to-text applications.
- Whisper Largehuggingface.coWhisper Large V2 is a robust automatic speech recognition model trained on 680,000 hours of multilingual and multitask supervised data. It supports transcription, translation, and language identification. The model is widely used via the Transformers library for building speech-to-text applications.
- Whisper Large V2huggingface.coWhisper Large V2 is a web application that transcribes audio files into text using a large-scale speech recognition model. Users can upload audio and receive accurate transcriptions, making it useful for transcription tasks and accessibility.
- Transcribe Audio to Text with Whisper1transcribe.com1Transcribe is a transcription tool for turning audio into text with OpenAI Whisper. It is presented as suitable for people handling long interviews, lectures, meetings, and court proceedings, and it offers a free way to try the service with no signup or credit card required. The service says it supports 99.9% accuracy and more than 99 languages, with automatic language detection. It accepts audio, video, PDF, and image uploads, and it also allows direct recording through the app. Other listed features include speaker identification, which labels different speakers in a transcript, and export to DOCX, PDF, SRT, or TXT. The page also says it can handle accents, background noise, and technical jargon, and that files can be up to 10 hours long and 5 GB in size. 1Transcribe is available on iOS, Android, web, Mac, and Windows. The page describes use across devices, including transcribing on a phone, editing on a laptop, and dictating on a Mac or PC. It says the latest Whisper models run on the company’s servers, so transcription works in a browser or app without API keys, setup, or GPU requirements. The service also mentions batch upload for up to five files at once, AI summaries and quizzes, secure cloud storage, and files being automatically deleted after 14 days. Pricing is listed as free for short files under five minutes, with longer files requiring a subscription. The monthly plan is US$19.99, and the yearly plan is US$49.99, with unlimited transcription minutes and the same feature set described on the pricing page. The page says plans auto-renew and can be canceled anytime. It also states that files are not used for AI training.
- Whisperhuggingface.coWhisper is a web application that enables users to transcribe or translate spoken audio into written text. Users can upload audio files, record directly, or provide YouTube links, and receive accurate transcriptions or translations. It is ideal for content creators, journalists, and researchers.
- Whisper Webwhisperweb.techWhisper Web is a browser-based transcription tool for converting audio, voice recordings, and YouTube videos into text. It produces transcripts with speaker labels and AI summaries, and it supports more than 100 languages. The service is free to try and does not require a credit card. The workflow centers on uploading audio or video files, pasting a YouTube URL, or recording from a microphone in the browser. Supported file types listed on the page include MP3, MP4, M4A, WAV, OGG, FLAC, and MOV, with files up to 2GB each. Whisper Web says it uses OpenAI Whisper, which provides timestamps and speaker labels, auto-detects languages, and works with mixed-language audio. It also states that the system handles clear audio, accents, crosstalk, and conference-room background noise. Output options include TXT, DOCX, PDF, SRT, VTT, and JSON. Transcripts are paired with a structured summary that highlights key points, action items, decisions, and quotes, and the summary feature includes 12 specialized templates. The page also says transcripts, text exports, and AI summaries can be sent to Notion and to Zapier-connected apps, and that exports can be pasted into Google Docs or Slack. It names use cases such as Zoom, Microsoft Teams, Google Meet, and Webex recordings, as well as meetings, sales calls, one-to-ones, and panel interviews. The site describes Whisper Web as free forever and free to try with two free transcriptions plus three AI summaries. It is browser-based, with no install, no plugin, no extension, and no IT ticket required. The page also states that audio is encrypted in transit, processed in isolation, deleted after transcription, and never used to train AI models.
- WhisperTranscribewhispertranscribe.comWhisperTranscribe is a web-based application that leverages Whisper AI models to transcribe audio files into text. It is designed for content creators and marketers who need fast, accurate transcription and integrated content creation tools.
- Whisper Smallhuggingface.cowhisper-small is an open-source automatic speech recognition model developed by OpenAI. It supports multilingual audio transcription and is suitable for developers and researchers building speech-to-text applications. The model can be fine-tuned and deployed locally or via API for various audio processing tasks.
- Whisper Large V3 Turbohuggingface.coopenai/whisper-large-v3-turbo is an advanced open-source speech recognition model that provides high-accuracy transcription for audio files in multiple languages. It is designed for developers and researchers building speech-to-text solutions and integrates easily with Python-based workflows.
- Whisper Largehuggingface.coThis is a GGUF-quantized version of OpenAI's Whisper Large V3 model optimized for use with transcribe.cpp. It supports automatic speech recognition across 100 languages. The quantized formats enable efficient local inference on consumer hardware while maintaining high transcription quality.
- WhisperAIwhisperai.comWhisperAI is a web and API-based platform for converting speech to text using AI, powered by OpenAI. It is designed for transcribing meetings, interviews, and notes with high accuracy and speed. Suitable for professionals and teams needing reliable voice transcription services.
- Whisper Large V3 Turbo WebGPUhuggingface.coWhisper Large V3 Turbo WebGPU is a browser-based speech recognition demo running the Whisper model using WebGPU acceleration. Users can record with their microphone or upload audio files to receive instant transcripts. It emphasizes on-device, privacy-preserving transcription without cloud dependency.
- Whisper Mediumhuggingface.coWhisper-medium is the 769M parameter version of OpenAI's Whisper speech recognition model family. It performs automatic speech recognition, language identification, and translation across many languages. The model is provided as open weights on Hugging Face and is widely used via the Transformers library for transcription and related audio tasks.
- Whisper Largehuggingface.coThis is a fine-tuned version of OpenAI's Whisper large-v3 model specialized for Hebrew (he) automatic speech recognition. Developed by ivrit-ai, it provides high-quality transcription for Hebrew audio and is available on Hugging Face for use with the Transformers library.
- Whisper Large V3huggingface.coWhisper Large V3 is a web application that converts spoken audio from recordings, uploads, or YouTube links into written text. It supports both transcription and translation, making it useful for content creators, researchers, and anyone needing accurate speech-to-text conversion.
- Audio Transcriptionhuggingface.coAudio Transcription is a web app that leverages the Whisper Large-v2 AI model to transcribe audio files into text. It offers fast and accurate transcription, supporting content creators, journalists, and professionals needing reliable speech-to-text conversion.
- Whisper Tinyhuggingface.coWhisper Tiny is an open-source automatic speech recognition (ASR) model developed by OpenAI. It enables developers to transcribe audio files into text across multiple languages, optimized for lightweight and efficient inference. The model is suitable for integration into speech-to-text pipelines and offline transcription tools.
- whisper-smithpypi.orgwhisper-smith is an open-source Python CLI tool for transcribing audio using OpenAI's speech-to-text APIs. It supports diarization and is designed for developers who need automated audio transcription workflows.
- Whisper Smallhuggingface.coThis is a converted version of OpenAI's Whisper-small model exported to ONNX format for use with Transformers.js and other ONNX runtimes. It performs automatic speech recognition, converting spoken audio into text in multiple languages. The model is designed for integration into web applications and environments where native PyTorch is not suitable.
- Whisper Large V3 Turbohuggingface.coThis is a converted version of the Whisper large-v3-turbo model in MLX format, optimized for Apple silicon. It performs automatic speech recognition (ASR) by transcribing audio to text. The model can be used locally with the mlx-whisper library and is suitable for developers building transcription tools or voice interfaces.
- Whisper Large V3 Turbohuggingface.coThis is a GGUF quantized version of the Whisper large v3 turbo model optimized for local inference using transcribe.cpp. It supports transcription and translation across 100 languages. The repository provides multiple quantization levels (F16, Q4, Q5, Q6, Q8) for different performance and accuracy tradeoffs on CPU and GPU hardware. It is intended for developers building offline speech recognition applications.
- Whisper Basehuggingface.coopenai/whisper-base is an open-source automatic speech recognition (ASR) model that transcribes audio files into text. It supports multiple languages and is designed for developers and researchers working on speech-to-text applications. The model is easy to integrate into Python workflows.
- whisper-localpypi.orgwhisper-local is a free, open-source AI dictation tool for Windows and macOS that transcribes speech to text entirely offline using Whisper models. It offers hotkey activation and privacy-focused local processing for users needing secure voice typing.
- Whisper Webhuggingface.coWhisper Web is a browser-based application that allows users to upload or record audio and receive instant transcriptions. The app supports multiple languages and provides editable text output, making it ideal for journalists, students, and anyone needing fast audio-to-text conversion.
- Whisper Transcriptiontomfun.coWhisper Transcription is a web-based application that converts audio and video files into text. It supports speaker diarization, URL-based transcription, and session management, making it useful for content creators, journalists, and researchers needing fast, accurate transcriptions.
- Whisper Tiny.enhuggingface.coopenai/whisper-tiny.en is the smallest English-only variant of OpenAI's Whisper automatic speech recognition model. It converts English audio into text with high accuracy while using minimal computational resources. Hosted on Hugging Face, it is widely used for testing, research, and lightweight transcription applications.
- Faster Whisper Largehuggingface.coThis is a conversion of OpenAI's Whisper large-v2 model to the CTranslate2 format for faster inference. It supports automatic speech recognition in 99 languages and can be used through the faster-whisper Python package. The model is provided in FP16 precision and is suitable for local transcription tasks.
- Distil Largehuggingface.codistil-whisper/distil-large-v3 is an open-source distilled version of the Whisper large-v3 model, optimized for significantly faster automatic speech recognition while maintaining high accuracy. Hosted on Hugging Face, it supports the Transformers library and is suitable for local or edge deployment. It has been evaluated on open ASR leaderboards and is used for efficient transcription tasks.
- Faster Whisper Large V3 Turbohuggingface.coThe faster-whisper-large-v3-turbo model is a conversion of OpenAI's Whisper large-v3-turbo to the CTranslate2 format hosted on Hugging Face. It enables speech-to-text transcription through the faster-whisper library and other CTranslate2-based projects. The repository provides the converted model weights along with example code for loading and running transcription. A typical usage imports the WhisperModel class from faster_whisper, instantiates the model with the repository identifier, calls the transcribe method on an audio file such as audio.mp3, and iterates over the resulting segments to access start time, end time, and text. The weights are stored in FP16 precision, which can be adjusted at load time through the compute_type option in CTranslate2. The conversion from the original OpenAI model was performed using the ct2-transformers-converter command-line tool. It is called automatically by the Mobius Labs fork of faster-whisper. The model carries an MIT license and is published by Dropbox Inc. No pricing information is stated because the model is distributed as an open artifact on the Hugging Face platform.
- Whisper Mediumhuggingface.coThis repository provides GGUF quantized versions of OpenAI's Whisper-medium model for use with transcribe.cpp and other GGUF-compatible runtimes. It supports transcription in 99 languages and can run efficiently on consumer hardware without requiring cloud services.
Ranked by how close each one sits to OpenAI Whisper in the index, not by popularity. Back to OpenAI Whisper →