11. A computer-implemented method, comprising: determining user profile data associated with a device; determining, in the user profile data, a first language spoken by a user associated with the user profile data; causing the device to output first audio, in the first language, soliciting a spoken utterance in a second language, wherein the first audio includes a first indicator representing an intent and a second indicator representing a content type; receiving, from the device, audio data corresponding to an utterance in the second language; performing automatic speech recognition (ASR) processing on the audio data to generate text data, the text data including a first portion and a second portion; associating the first portion with the first indicator; associating the second portion with the second indicator; generating a third indicator representing the text data corresponds to the second language; using the first portion associated with the first indicator, the second portion associated with the second indicator, and the third indicator to train a natural language understanding (NLU) component corresponding to the second language; after training the NLU component, determining, using the NLU component, that a user input corresponds to the intent and the content type; and causing an application to perform an action based at least in part on determining that the user input corresponds to the intent and the content type.
13. The computer-implemented method of claim 11 , further comprising: generating second text data soliciting the spoken utterance; and performing text-to-speech (TTS) processing on the second text data to create first output audio data, wherein the first audio corresponds to the first output audio data.