Speech-to-Text (STT)

The STT layer transcribes participant speech in real time using automatic speech recognition (ASR). You can select a model optimized for your use case and language requirements.

STT models

Select an STT model using the stt_engine parameter in the layers.stt object. The following models are available:

Model	Description
`tavus-auto` (default)	Automatically selects the best STT model for the conversation’s language. Recommended for most use cases.
`tavus-parakeet`	Highest throughput, lowest latency for English and European languages.
`tavus-soniox`	Purpose-built for Indian languages with broad multilingual coverage.
`tavus-whisper`	Broad multilingual coverage across all supported languages.
`tavus-deepgram-medical`	Domain-specific English STT optimized for clinical and healthcare vocabulary. English only.
`tavus-advanced`	Deprecated. Still active but not recommended for new integrations.

tavus-auto is the default. Use it unless you have a specific language or domain requirement. It automatically routes to the best model for each conversation.

Choosing the right model

A language is listed for a model only if both STT and TTS coverage are available.

Category	Recommended model	Supported languages
General purpose	`tavus-auto`	All 43 languages
Indic languages	`tavus-soniox`	Bengali, English, Gujarati, Hindi, Kannada, Malayalam, Marathi, Punjabi, Tamil, Telugu + broad support for all other languages
English + European	`tavus-parakeet`	Bulgarian, Croatian, Czech, Danish, Dutch, English, Finnish, French, German, Greek, Hungarian, Italian, Polish, Portuguese, Romanian, Russian, Slovak, Spanish, Swedish, Ukrainian
Broad multilingual	`tavus-whisper` or `tavus-soniox`	All 43 languages
Medical (English)	`tavus-deepgram-medical`	English

Using Smart Language Detection requires either tavus-auto, tavus-soniox, or tavus-whisper.

Configuring the STT layer

Define the STT layer under the layers.stt object.

`stt_engine`

Set the STT model for transcription:

"stt": {
  "stt_engine": "tavus-auto"
}

`hotwords`

Use this to prioritize certain names or terms that are difficult to transcribe.

"hotwords": "Roey is the name of the person you're speaking with."

The above helps the model transcribe “Roey” correctly instead of “Rowie.”

Use hotwords for proper nouns, brand names, or domain-specific language that standard STT engines might struggle with.

Example configuration

Below is an example PAL with a configured STT layer using the recommended tavus-auto engine:

{
  "pal_name": "Customer Service Agent",
  "system_prompt": "You assist users by listening carefully and providing helpful answers.",
  "pipeline_mode": "full",
  "default_face_id": "r90bbd427f71",
  "layers": {
    "stt": {
      "stt_engine": "tavus-auto",
      "hotwords": "Roey is the name of the person you're speaking with."
    }
  }
}

Refer to the Create PAL API for a complete list of supported fields.

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Speech-to-Text (STT)

STT models

Choosing the right model

Configuring the STT layer

`stt_engine`

`hotwords`

Example configuration

​STT models

​Choosing the right model

​Configuring the STT layer

​stt_engine

​hotwords

​Example configuration

STT models

Choosing the right model

Configuring the STT layer

`stt_engine`

`hotwords`

Example configuration