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

# Verbatim Tags

Alphanumeric strings — booking references, license plates, serial numbers, IDs — can be ambiguous for a TTS model: `AHAA7771Z` might be read as a word, a number, or a mix of both. Wrap a sequence in `<verbatim>` tags to have it spelled out character by character: letters as letter names, digits as single digits, and symbols by name (for example, `@` is read as "at").
**Example:**

```
Your booking reference is <verbatim>AHAA7771Z</verbatim>.
```

The tagged sequence is read as "A H A A seven seven seven one Z" instead of being read as a word or a number.

**Constraints:**

* Use well-formed tags with the sequence inside: `<verbatim>AHAA7771Z</verbatim>`. Tag names are **case insensitive**; `<say-as interpret-as="verbatim">` is an equivalent, SSML-standard spelling of the same tag.
* Keep the content to letters, digits, spaces, and these symbols: `( ) - # : . , + @ / _ *`. Tags containing other characters may be read as regular text instead of being spelled out.
* Verbatim tags require [text normalization](/tts/best-practices/prompting-for-tts#notes-on-normalization) to be enabled. If `applyTextNormalization` is set to `OFF`, the tags are removed and their content is read as regular text.
* Expansion is currently English-oriented: characters are read with English letter and number names.

<Note>
  Verbatim tags are most reliable on `inworld-tts-2` — we recommend it for alphanumeric-heavy content. As with any generative TTS, exact renditions can vary; keep tagged sequences short where possible and verify output for your use case.
</Note>