POST /v1/audio/transcriptions — Speech-to-Text API

The /v1/audio/transcriptions endpoint converts speech recordings into text using open-weight transcription models including Whisper and Voxtral, all served from Meliai’s European provider network. The endpoint accepts multipart/form-data uploads and is compatible with the OpenAI Audio Transcriptions API, so existing integrations migrate with a single base_url change. You can optionally specify the language and provide a prompt to improve accuracy for domain-specific vocabulary.

Endpoint

POST https://api.meliai.ai/v1/audio/transcriptions

Authorization: Bearer sk-mel-<KEY> via Authorization header.
Content-Type: multipart/form-data

Parameters

string

required

The transcription model ID to use. Whisper-family and Voxtral models available on the Meliai network are listed under GET /v1/models. Check model capabilities for supported languages and audio formats.

file

required

The audio file to transcribe, submitted as a multipart/form-data field. Supported formats include MP3, MP4, MPEG, MPGA, M4A, WAV, and WEBM. Maximum file size depends on the model and provider.

string

ISO 639-1 language code of the audio (e.g. "en", "de", "fr", "nl"). When omitted, the model auto-detects the language. Providing the correct language code improves accuracy and reduces latency.

string

Format of the transcription output:

"json" — {"text": "..."} (default)
"text" — plain text string
"srt" — SubRip subtitle format with timestamps
"vtt" — WebVTT subtitle format with timestamps

string

Optional context string to guide the transcription. Use this to provide domain-specific vocabulary, speaker names, or abbreviations the model should recognise. The prompt is not included in the output.

Examples

curl https://api.meliai.ai/v1/audio/transcriptions \
  -H "Authorization: Bearer $MELIAI_API_KEY" \
  -F model="<WHISPER_MODEL_ID>" \
  -F file="@recording.mp3" \
  -F language="en"

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["MELIAI_API_KEY"],
    base_url="https://api.meliai.ai/v1",
)

with open("recording.mp3", "rb") as f:
    transcript = client.audio.transcriptions.create(
        model="<WHISPER_MODEL_ID>",
        file=f,
        language="en",
    )
print(transcript.text)

import OpenAI from "openai";
import fs from "fs";

const client = new OpenAI({
  apiKey: process.env.MELIAI_API_KEY,
  baseURL: "https://api.meliai.ai/v1",
});

const transcript = await client.audio.transcriptions.create({
  model: "<WHISPER_MODEL_ID>",
  file: fs.createReadStream("recording.mp3"),
  language: "en",
});
console.log(transcript.text);

Request subtitles

Pass response_format: "srt" or "vtt" to receive timestamped subtitles — useful for captioning video content.

with open("presentation.mp4", "rb") as f:
    subtitles = client.audio.transcriptions.create(
        model="<WHISPER_MODEL_ID>",
        file=f,
        response_format="vtt",
    )
print(subtitles)

curl https://api.meliai.ai/v1/audio/transcriptions \
  -H "Authorization: Bearer $MELIAI_API_KEY" \
  -F model="<WHISPER_MODEL_ID>" \
  -F file="@presentation.mp4" \
  -F response_format="vtt"

Domain-specific vocabulary

Use the prompt field to improve recognition of unusual terms:

with open("medical_dictation.mp3", "rb") as f:
    transcript = client.audio.transcriptions.create(
        model="<WHISPER_MODEL_ID>",
        file=f,
        language="en",
        prompt="Medical dictation. Terms: GDPR, DPIA, pseudonymisation, EHR.",
    )
print(transcript.text)

Response

For the default "json" response format:

{
  "text": "Transcribed text here.",
  "environment_impact": {
    "energy_kwh": 0.000095,
    "carbon_g_co2": 0.0068,
    "water_liters": 0.00038,
    "renewable_percent": 92,
    "pue": 1.19,
    "provider_id": "provider-eu-central",
    "location": "Frankfurt, DE"
  },
  "billing_cost": {
    "energy": 0.000047,
    "credits": 0.00076,
    "paid_with": "credits"
  }
}

For "text" format, the response body is the plain transcript string. For "srt" and "vtt", the body is the subtitle file content.

string

The full transcribed text. Present in "json" response format.

object

Per-request environmental footprint. Fields: energy_kwh, carbon_g_co2, water_liters, renewable_percent, pue, provider_id, location. Present in "json" format responses.

object

Itemised cost: energy (EUR), credits deducted, and paid_with. Present in "json" format responses.

Providing the language parameter is strongly recommended for production use. Auto-detection adds a small amount of latency and can occasionally misidentify short audio clips.

Audio transcription runs on GDPR-compliant European infrastructure. Audio files and transcripts never leave the EU and are never used to train models.

Overview

Inference

Batch & Files

Models

POST /v1/audio/transcriptions — Speech-to-Text API

Endpoint

Parameters

Examples

Request subtitles

Domain-specific vocabulary

Response

​Endpoint

​Parameters

​Examples

​Request subtitles

​Domain-specific vocabulary

​Response

Endpoint

Parameters

Examples

Request subtitles

Domain-specific vocabulary

Response