Glossary · AI & Agents
Whisper
Overview
What Whisper is
Whisper is an automatic speech recognition (ASR) model from OpenAI, released as open source in 2022. It transcribes spoken audio into text and can also translate speech from other languages into English, with strong multilingual coverage.
It is distributed under a permissive MIT license, so teams can run the model weights on their own hardware. OpenAI also exposes Whisper-based transcription through its hosted API for those who prefer not to self-host.
How Whisper works
Whisper is an encoder-decoder transformer trained on a large, diverse dataset of audio paired with text. It comes in multiple sizes, from tiny through large, where larger models are more accurate but slower and more resource-hungry; community variants like faster-whisper optimize inference speed.
Whisper was designed primarily for transcribing complete audio files rather than low-latency live streaming. Real-time use is possible by chunking audio, but purpose-built streaming APIs often deliver lower latency for interactive voice agents.
Where it fits in a voice-AI stack
Whisper is a candidate for the speech-to-text component of a voice or automation pipeline, turning recordings or call audio into text for a language model, search index, or RAG knowledge base. Its self-hostable weights make it attractive when data privacy or cost control rules out sending audio to a third-party API.
For live phone agents, weigh Whisper against streaming-first options like Deepgram and AssemblyAI, or against speech-to-speech models such as the OpenAI Realtime API that fold transcription into the model itself.
Where we use it
Related Zen in Tech services
How our team puts Whisper to work in real projects.
FAQ
Whisper — common questions
What is Whisper used for?
Whisper is used to transcribe and translate speech into text. Common uses include captioning and subtitling, transcribing meetings and calls, and preparing audio content for search or retrieval-augmented generation (RAG).
Is Whisper free to use?
The Whisper model is open source under an MIT license, so you can run it yourself at no licensing cost (you still pay for compute). OpenAI also offers a paid hosted transcription API based on Whisper for teams that prefer not to self-host.
Can Whisper do real-time transcription?
Whisper was built mainly for transcribing complete audio files, not live streaming. Real-time use is possible by feeding it short audio chunks, but streaming-first APIs like Deepgram or AssemblyAI usually offer lower latency for interactive voice agents.
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