Keyterm prompting

Keyterm prompting is a feature that allows you to highlight words or phrases to bias the model towards transcribing them. This is useful for transcribing specific words or sentences that are not common in the audio, such as product names, names, or other specific terms. Keyterms are more powerful than biased keywords or customer vocabularies offered by other models, because it relies on the context to decide whether to transcribe that term or not.

For example, if your company name is not a common phrase or has a unique spelling or pronunciation you can use keyterms to ensure the model transcribes correctly. Take the following audio:

Without keyterm prompting, the model might transcribe the above as:

I work at eleven labs.

Which uses the wrong style for the company name. With keyterm prompting, you can ensure the model transcribes the above with the correct spelling and style:

I work at ElevenLabs.

The model is able to use context to determine whether a term should be transcribed or not. When providing the keyterm "ElevenLabs", the above audio transcribes as expected, yet the model will still be able to transcribe the following correctly based on the context:

Which outputs the following transcription:

I've worked at many labs. In fact I've worked at eleven labs.

Keyterm prompting is integrated into the batch Speech to Text API by passing the keyterms parameter to the convert method.

import osfrom dotenv import load_dotenvfrom io import BytesIOimport requestsfrom elevenlabs.client import ElevenLabsload_dotenv()elevenlabs = ElevenLabs(    api_key=os.getenv("ELEVENLABS_API_KEY"),)audio_url = (    "https://storage.googleapis.com/eleven-public-cdn/documentation_assets/audio/stt-keyterm-prompting.mp3")response = requests.get(audio_url)audio_data = BytesIO(response.content)transcription = elevenlabs.speech_to_text.convert(    file=audio_data,    model_id="scribe_v2", # Model to use    # Keyterms to prompt the model with.    # Up to 1000 keyterms can be provided, with a maximum length of 50 characters each    keyterms=["ElevenLabs"],)print(transcription)

import { ElevenLabsClient } from "@elevenlabs/elevenlabs-js";import "dotenv/config";const elevenlabs = new ElevenLabsClient({  apiKey: process.env.ELEVENLABS_API_KEY,});const response = await fetch(  "https://storage.googleapis.com/eleven-public-cdn/documentation_assets/audio/stt-keyterm-prompting.mp3");const audioBlob = new Blob([await response.arrayBuffer()], { type: "audio/mp3" });const transcription = await elevenlabs.speechToText.convert({  file: audioBlob,  modelId: "scribe_v2", // Model to use  // Keyterms to prompt the model with.  // Up to 1000 keyterms can be provided, with a maximum length of 50 characters each  keyterms: ["ElevenLabs"],});console.log(transcription);

Keyterm prompting is also available for the realtime Speech to Text WebSocket API. Pass the keyterms parameter when connecting.

connection = await elevenlabs.speech_to_text.realtime.connect(RealtimeUrlOptions(
    model_id="scribe_v2_realtime",
    keyterms=["ElevenLabs"],
))

const connection = await elevenlabs.speechToText.realtime.connect({
  modelId: "scribe_v2_realtime",
  keyterms: ["ElevenLabs"],
});

When using the WebSocket API directly, pass keyterms as query parameters:

wss://api.elevenlabs.io/v1/speech-to-text/realtime?model_id=scribe_v2_realtime&keyterms=ElevenLabs&keyterms=AnotherTerm

Full Speech to Text API reference and parameters.

Automatically detect and label entities like names, dates, and locations in transcripts.