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Audio Classification

Audio classification is the task of assigning a label or class to a given audio.

Example applications:

- Recognizing which command a user is giving
- Identifying a speaker
- Detecting the genre of a song

> For more details about the `audio-classification` task, check out its dedicated page! You will find examples and related materials.

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Recommended models

Explore all available models and find the one that suits you best here.

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Using the API

There are currently no snippet examples for the audio-classification task, as no providers support it yet.

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API specification

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Request

Headers |  |
--- | --- | ---
authorization | string | Authentication header in the form `'Bearer: hf_****'` when `hf_****` is a personal user access token with “Inference Providers” permission. You can generate one from your settings page.

Payload |  |
--- | --- | ---
inputs* | string | The input audio data as a base64-encoded string. If no `parameters` are provided, you can also provide the audio data as a raw bytes payload.
parameters | object |
function_to_apply | enum | Possible values: sigmoid, softmax, none.
top_k | integer | When specified, limits the output to the top K most probable classes.

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Response

Body |  |
--- | --- | ---
(array) | object[] | Output is an array of objects.
label | string | The predicted class label.
score | number | The corresponding probability.

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