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

# Multilingual support

> How to configure different languages

# Multilingual Support

The vocode project can be configured to support multiple languages for speech synthesis and automatic speech recognition (ASR).

## Speech Synthesis

The speech synthesizer used in vocode is configurable. By default, the `AzureSynthesizer` is used which supports [over 75 voices across over 45 languages](https://docs.microsoft.com/en-us/azure/cognitive-services/speech-service/language-support?tabs=tts).

To configure a different language, modify the `SynthesizerConfig` when initializing the conversation:

```python theme={null}
from vocode.streaming.models.synthesizer import AzureSynthesizerConfig

synthesizer_config = AzureSynthesizerConfig(
    voice_name="de-DE-KatjaNeural" # German voice
    language_code="de-DE" # Language of text to be synthesized
)
```

## Transcription

The transcriber used in vocode is also configurable. By default, `DeepgramTranscriber` is used which supports [over 35 languages](https://developers.deepgram.com/docs/languages-overview).

To configure a different language model, modify the language code passed to `TranscriberConfig` when initializing the config object (`en-US` is the default):

```python theme={null}
from vocode.streaming.models.transcriber import DeepgramTranscriberConfig

transcriber_config = DeepgramTranscriberConfig(
    language="es" # Spanish
    model="nova-2" # Most languages are supported on the Nova 2 model
)
```

***Note: the default model for Deepgram is Nova, so you must pass `model="nova-2"` to use that model.***

Other transcription services like Google Cloud Speech or Assembly AI could also be used by configuring the appropriate `TranscriberConfig`.

## Language Configuration

It is recommended to load the speech synthesizer voice and transcription model from environment variables or configuration to avoid hard-coding language choices:

```python theme={null}
import os
from vocode.streaming.models.synthesizer import AzureSynthesizerConfig
from vocode.streaming.models.transcriber import DeepgramTranscriberConfig

SYNTHESIZER_VOICE = os.getenv("SYNTHESIZER_VOICE", default="en-US-AriaNeural")
ASR_MODEL = os.getenv("DEEPGRAM_MODEL", default="en-US")

synthesizer_config = AzureSynthesizerConfig(voice=SYNTHESIZER_VOICE)
transcriber_config = DeepgramTranscriberConfig(model=DEEPGRAM_MODEL)
```

This allows dynamically configuring the speech language without code changes.