Compare Hindi Speech Recognition

Which AI model actually works best for your needs? Upload your own data and evaluate any Gooey.AI workflow, LLM or AI model against any other. Great for large data sets, AI model evaluation, task automation, parallel processing and automated testing. To get started, paste in a Gooey.AI workflow, upload a CSV of your test data (with header names!), check the mapping of headers to workflow inputs and tap Submit. More tips in the Details below.


Gooey Workflows

Provide one or more Gooey.AI workflow runs.
You can add multiple runs from the same recipe (e.g. two versions of your copilot) and we'll run the inputs over both of them.

Speech Recognition and Translation

Whisper v2 (auto detect)

Speech Recognition and Translation

Whisper Hindi Large v2 (Bhashini)

Speech Recognition and Translation

Whisper v3 (with english translation)

Speech Recognition and Translation

Conformer Hindi (ai4bharat)

Speech Recognition and Translation

Chirp/USM (Google)

Speech Recognition and Translation

Deepgram

Speech Recognition and Translation

Azure - Hindi (Microsoft)

Speech Recognition and Translation

Seamless4MT (facebook)


Input Data Spreadsheet

Upload or link to a CSV or google sheet that contains your sample input data.
For example, for Copilot, this would sample questions or for Art QR Code, would would be pairs of image descriptions and URLs.
Remember to includes header names in your CSV too.

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Columns

Please select which CSV column corresponds to your workflow's input fields.
For the outputs, select the fields that should be included in the output CSV.
To understand what each field represents, check out our API docs.

Inputs

audios

Outputs

Evaluation Workflows

(optional) Add one or more Gooey.AI Evaluator Workflows to evaluate the results of your runs.

Low Resource ASR Evaluator


Run cost = 1 credits

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