> ## Documentation Index
> Fetch the complete documentation index at: https://assemblyai.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Add transcription context

> Improve a voice agent's transcription accuracy for domain terms with a contextual prompt and a key terms list.

Two levers make the agent's **speech-to-text** transcribe the caller more accurately: a free-form **transcription prompt** that describes the call, and a **key terms** list of exact words to boost. Use them together: the prompt sets the scene, and key terms nail specific names and codes. Both live under `input`, set when you [create](/docs/voice-agents/voice-agent-api/create-agent) or [update](/docs/voice-agents/voice-agent-api/manage-agents) the agent, or inline via [`session.update`](/docs/voice-agents/voice-agent-api/session-configuration). For how both work under the hood, see [Prompting and keyterms](/docs/streaming/prompting-and-keyterms) in the Streaming docs.

## Contextual prompt

`input.transcription_prompt` tells the speech-to-text model what the call is about so it resolves jargon, product names, and homophones in what the caller says. Describe the domain and scenario in plain language.

<Note>
  This is **not** the same as `system_prompt`. `system_prompt` shapes what the **agent says**; `transcription_prompt` shapes how the caller's speech is **transcribed**. Give it context ("this is a pharmacy support call"), not instructions ("use formal punctuation"); behavioral commands are ignored.
</Note>

<CodeGroup>
  ```bash cURL {9} theme={null}
  curl -X POST https://agents.assemblyai.com/v1/agents \
    -H "Authorization: $ASSEMBLYAI_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{
      "name": "Pharmacy Assistant",
      "system_prompt": "You help patients with prescription refills.",
      "voice": { "voice_id": "alba" },
      "input": {
        "transcription_prompt": "A pharmacy support call. Callers mention medication names, dosages in mg, insurance carriers, and pharmacy locations."
      }
    }'
  ```

  ```python Python {13} theme={null}
  # pip install requests
  import os
  import requests

  resp = requests.post(
      "https://agents.assemblyai.com/v1/agents",
      headers={"Authorization": os.environ["ASSEMBLYAI_API_KEY"]},
      json={
          "name": "Pharmacy Assistant",
          "system_prompt": "You help patients with prescription refills.",
          "voice": {"voice_id": "alba"},
          "input": {
              "transcription_prompt": "A pharmacy support call. Callers mention medication names, dosages in mg, insurance carriers, and pharmacy locations."
          },
      },
  )
  resp.raise_for_status()
  print(resp.json())
  ```

  ```javascript Node.js {13} theme={null}
  // Node 18+ has fetch built in
  const res = await fetch("https://agents.assemblyai.com/v1/agents", {
    method: "POST",
    headers: {
      Authorization: process.env.ASSEMBLYAI_API_KEY,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({
      name: "Pharmacy Assistant",
      system_prompt: "You help patients with prescription refills.",
      voice: { voice_id: "alba" },
      input: {
        transcription_prompt:
          "A pharmacy support call. Callers mention medication names, dosages in mg, insurance carriers, and pharmacy locations.",
      },
    }),
  });
  const data = await res.json();
  console.log(data);
  ```
</CodeGroup>

| Field                        | Type   | Required | Notes                                                                           |
| ---------------------------- | ------ | -------- | ------------------------------------------------------------------------------- |
| `input.transcription_prompt` | string | No       | Free-form context about the call, up to 1750 characters. Updatable mid-session. |

## Key terms

`input.keyterms` is an explicit list of rare or domain-specific words to boost, like a person's name, a product, or an acronym. It works as a word boost, biasing the speech recognition model toward each term. Reach for it when you have specific strings to nail, and use the prompt above for the surrounding context.

<CodeGroup>
  ```bash cURL {8} theme={null}
  curl -X POST https://agents.assemblyai.com/v1/agents \
    -H "Authorization: $ASSEMBLYAI_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{
      "name": "Support Assistant",
      "system_prompt": "You are a friendly support agent. Keep replies under two sentences.",
      "voice": { "voice_id": "alba" },
      "input": { "keyterms": ["AssemblyAI", "Lemur", "Ozempic"] }
    }'
  ```

  ```python Python {12} theme={null}
  # pip install requests
  import os
  import requests

  resp = requests.post(
      "https://agents.assemblyai.com/v1/agents",
      headers={"Authorization": os.environ["ASSEMBLYAI_API_KEY"]},
      json={
          "name": "Support Assistant",
          "system_prompt": "You are a friendly support agent. Keep replies under two sentences.",
          "voice": {"voice_id": "alba"},
          "input": {"keyterms": ["AssemblyAI", "Lemur", "Ozempic"]},
      },
  )
  resp.raise_for_status()
  print(resp.json())
  ```

  ```javascript Node.js {12} theme={null}
  // Node 18+ has fetch built in
  const res = await fetch("https://agents.assemblyai.com/v1/agents", {
    method: "POST",
    headers: {
      Authorization: process.env.ASSEMBLYAI_API_KEY,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({
      name: "Support Assistant",
      system_prompt: "You are a friendly support agent. Keep replies under two sentences.",
      voice: { voice_id: "alba" },
      input: { keyterms: ["AssemblyAI", "Lemur", "Ozempic"] },
    }),
  });
  const data = await res.json();
  console.log(data);
  ```
</CodeGroup>

| Field            | Type              | Required | Notes                                                                  |
| ---------------- | ----------------- | -------- | ---------------------------------------------------------------------- |
| `input.keyterms` | string\[] \| null | No       | Up to 100 transcription-bias strings. `null` or `[]` clears the boost. |

**Add:**

* Brand, product, and feature names that aren't in everyday English (`"AssemblyAI"`, `"Lemur"`, `"Ozempic"`).
* Proper nouns specific to this caller: their full name, their account holder's name, the agent's name if it's unusual.
* Domain jargon the model might otherwise transcribe as a common-word homophone (`"hemochromatosis"`, `"polysomnography"`).
* Acronyms you want spelled in full (`"PCI DSS"`, `"FedRAMP"`).

**Don't add:**

* Common English words. Each entry boosts that string, and adding common words at the same weight as your rare terms dilutes the boost.
* Whole sentences or phrases. The boost is per-term, not per-phrase.
* Punctuation, formatting, or instructions. The list is transcription hints, not prompt context.

Replace the list any time by sending a new `keyterms` array; it takes effect on the next user utterance. Refresh it when the conversation enters a new domain, for example when a support call moves from billing to technical.