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whisper

Model ID: @cf/openai/whisper

Automatic speech recognition (ASR) system trained on 680,000 hours of multilingual and multitask supervised data

More Information  

​​ Properties

Task Type: Automatic Speech Recognition

​​ Code Examples

Workers - TypeScript
export interface Env {
AI: Ai;
}
export default {
async fetch(request: Request, env: Env) {
const res: any = await fetch(
"https://github.com/Azure-Samples/cognitive-services-speech-sdk/raw/master/samples/cpp/windows/console/samples/enrollment_audio_katie.wav"
);
const blob = await res.arrayBuffer();
const input = {
audio: [...new Uint8Array(blob)],
};
const response = await env.AI.run(
"@cf/openai/whisper",
input
);
return Response.json({ input: { audio: [] }, response });
},
};
curl
curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/run/@cf/openai/whisper \
-X POST \
-H "Authorization: Bearer $CLOUDFLARE_API_TOKEN" \
--data-binary "@talking-llama.mp3"

​​ Response

Automatic speech recognition responses return both a single string text property with the audio transciption and an optional array of words with start and end timestamps if the model supports that.

Here’s an example of the output from the @cf/openai/whisper model:

{
"text": "It is a good day",
"word_count": 5,
"words": [
{
"word": "It",
"start": 0.5600000023841858,
"end": 1
},
{
"word": "is",
"start": 1,
"end": 1.100000023841858
},
{
"word": "a",
"start": 1.100000023841858,
"end": 1.2200000286102295
},
{
"word": "good",
"start": 1.2200000286102295,
"end": 1.3200000524520874
},
{
"word": "day",
"start": 1.3200000524520874,
"end": 1.4600000381469727
}
]
}