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openai/whisper-1Transcription at 13 credits a minute
Whisper transcribes speech in many languages, including accented and code-switched French, and returns timestamps. Billed per started minute of audio.
Automatic language detection
99%+ accuracy on clean audio
Accepts MP4, WebM and other video formats
Text, SRT or VTT output
Team meeting transcription
Podcast episode transcription
Yes. Top up your Tchavi account with Orange Money, MTN MoMo, M-Pesa or another mobile money operator. No bank card is needed. Credits land as soon as the payment is confirmed and are deducted as you use them.
Yes. Keep your current OpenAI SDK, just change the base URL to Tchavi's (shown in the API tab) and use your Tchavi key. The rest of your code stays the same.
import Tchavi from '@tchavi/sdk';
import fs from 'fs';
const client = new Tchavi({ apiKey: 'API_KEY' });
const response = await client.audio.speech.create({
"model": "whisper-1",
"input": "Hello, world!",
"voice": "alloy",
"response_format": "mp3"
});
const buffer = Buffer.from(await response.arrayBuffer());
fs.writeFileSync('speech.mp3', buffer);
console.log('X-Credits-Used:', response.headers.get('x-credits-used'));Every parameter this model accepts on the API. Check the SDK for full typings.
modelRequiredTTS model (e.g. `whisper-1`).
inputRequiredThe text to synthesize.
voiceRequiredVoice timbre: `alloy`, `ash`, `ballad`, `cedar`, `coral`, `echo`, `fable`, `marin`, `nova`, `onyx`, `sage`, or `shimmer`.
response_format"mp3"Audio container format.
speed1.0Playback speed multiplier.