Transcribe audio files through 9Router using models from providers such as OpenAI, Groq, and Deepgram. Receive plain text, structured results with timestamps, or SRT and VTT subtitles, depending on the selected model’s support.
Speech-to-text via 9Router /v1/audio/transcriptions using OpenAI Whisper / Groq / Gemini / Deepgram / AssemblyAI / NVIDIA / HuggingFace models. Use when the user wants to transcribe audio, convert speech to text, or get subtitles from audio files.
Review the instructions the agent will receive before you install.
Requires NINEROUTER_URL (and NINEROUTER_KEY if auth enabled). See https://raw.githubusercontent.com/decolua/9router/refs/heads/master/skills/9router/SKILL.md for setup.
curl $NINEROUTER_URL/v1/models/stt | jq '.data[].id'
# Per-model params (language, response_format, prompt, temperature support)
curl "$NINEROUTER_URL/v1/models/info?id=openai/whisper-1"
model = STT model ID (e.g. openai/whisper-1, groq/whisper-large-v3, deepgram/nova-3, gemini/gemini-2.5-flash).
POST $NINEROUTER_URL/v1/audio/transcriptions (OpenAI Whisper compatible, multipart/form-data)
| Field | Required | Notes |
|---|---|---|
model | yes | from /v1/models/stt |
file | yes | audio file (mp3, wav, m4a, webm, ogg, flac) |
language | no | ISO-639-1 (e.g. en, vi) |
prompt | no | hint text to guide transcription |
response_format | no | json (default) / text / verbose_json / srt / vtt |
temperature | no | 0–1 |
curl -X POST "$NINEROUTER_URL/v1/audio/transcriptions" \
-H "Authorization: Bearer $NINEROUTER_KEY" \
-F "model=openai/whisper-1" \
-F "file=@audio.mp3" \
-F "language=vi"
JS (Node):
import { createReadStream } from "node:fs";
const form = new FormData();
form.append("model", "groq/whisper-large-v3-turbo");
form.append("file", new Blob([await (await import("node:fs/promises")).readFile("audio.mp3")]), "audio.mp3");
const r = await fetch(`${process.env.NINEROUTER_URL}/v1/audio/transcriptions`, {
method: "POST",
headers: { "Authorization": `Bearer ${process.env.NINEROUTER_KEY}` },
body: form,
});
const { text } = await r.json();
console.log(text);
Default (response_format=json):
{ "text": "Xin chào, đây là bản ghi âm." }
verbose_json adds language, duration, segments[] with timestamps.
srt / vtt return subtitle text.
| Provider | model format | Notes |
|---|---|---|
openai | whisper-1, gpt-4o-transcribe, gpt-4o-mini-transcribe | Native OpenAI shape |
groq | whisper-large-v3, whisper-large-v3-turbo, distil-whisper-large-v3-en | Fastest; OpenAI shape |
gemini | gemini-2.5-flash, gemini-2.5-pro, gemini-2.5-flash-lite | Server converts to generateContent with audio inline |
deepgram | nova-3, nova-2, whisper-large | Token auth; server adapts response |
assemblyai | universal-3-pro, universal-2 | Async upload+poll handled server-side |
nvidia | nvidia/parakeet-ctc-1.1b-asr | NIM endpoint |
huggingface | openai/whisper-large-v3, openai/whisper-small | HF Inference API |
elevenlabs | scribe_v1, scribe_v2 | Whisper-compatible shape; xi-api-key auth, not Bearer. Extra params: timestamps_granularity (word/character/none), tag_audio_events, and speaker labelling via either diarize=true or num_speakers (1–32) — sending both makes the request invalid, so diarize wins and num_speakers is dropped. Blank language is omitted upstream for auto-detect. srt/vtt and verbose_json segments are served from Scribe's own additional_formats render, so segments[] is omitted when the upstream render is unavailable rather than synthesized. Does not accept temperature or prompt — those are not forwarded. |
No reviews yet. Tell others what you thought.
No login needed. Share how it worked for you, ask a question, or note where it did not run.
No comments yet. Be the first to write one.
Set up access to 9Router, a shared gateway for multiple AI providers, and discover available models. Find the relevant capability skills for chat, images, speech, embeddings, web search, and webpage retrieval.
Ask AI questions, generate code, and summarize text through 9Router using OpenAI or Anthropic request formats. Receive responses incrementally with streaming, and use provider combinations that automatically try another provider when needed.
Turn text into embeddings, numeric representations of meaning, through 9Router. Choose a model and process individual texts or batches to prepare data for meaning-based search, similarity comparisons, or RAG systems that retrieve reference material.
Generate images from written descriptions through 9Router using a choice of image models. Check each model’s supported settings, request an image, and receive a URL, encoded image data, or image bytes for saving to a file.
Convert written text into speech through 9Router, choosing from multiple voice providers. Check available models and voices, then generate MP3 audio for narration, voiceovers, or reading text aloud.
Create videos from text or images through 9Router using xAI Grok Imagine. Set duration, aspect ratio, and resolution, then track the generation job and download the completed video as an MP4 file.