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This guide walks you through a complete end-to-end example: uploading an audio file to Dolva and receiving analysis results. By the end, you’ll have made a real API call and understand the shape of the response.

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What You Need

  • A Dolva API token (from your dashboard at dolva.ai)
  • An audio file to analyze (WAV, MP3, or similar — see Audio Requirements)
  • curl, Python 3, or Node.js

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Step 1: Pick Your Analysis Type

Dolva offers two analysis endpoints:
  • /v1/analyze/cognitive — for cognitive load, clarity, and processing signals
  • /v1/analyze/emotion — for emotional state and valence signals
You can call both on the same audio file. Start with whichever is most relevant to your use case.

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Step 2: Make the Request

Replace dv-xxxxxxxx with your token and /path/to/audio.wav with your file path: 
curl -X POST https://api.dolva.ai/v1/analyze/cognitive \
  -H "Authorization: Bearer dv-xxxxxxxx" \
  -F "audio=@/path/to/audio.wav"

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Step 3: Read the Response

A successful request returns HTTP 200 with a JSON body containing the analysis signals:
Example Response
{
  "status": "ok",
  "signals": {
    "cognitive_load": 0.68,
    "clarity": 0.81
  }
}
The exact fields returned depend on the Dolva model version and the content of your audio. See Interpreting Results for a detailed explanation of each field.

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Step 4: Try Emotion Analysis

Repeat the same request against the emotion endpoint to see affective signals:
curl
curl -X POST https://api.dolva.ai/v1/analyze/emotion \
  -H "Authorization: Bearer dv-xxxxxxxx" \
  -F "audio=@/path/to/audio.wav"

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What’s Next

Interpreting Results

Understand what each signal value means.

Error Handling

Handle errors and edge cases in production.