@mastra/core/dist/docs/references/docs-voice-speech-to-text.md

Mastra is a framework for building AI-powered applications and agents with a modern TypeScript stack.

# Speech-to-Text (STT)

Speech-to-Text (STT) in Mastra provides a standardized interface for converting audio input into text across multiple service providers. STT helps create voice-enabled applications that can respond to human speech, enabling hands-free interaction, accessibility for users with disabilities, and more natural human-computer interfaces.

## Configuration

To use STT in Mastra, you need to provide a `listeningModel` when initializing the voice provider. This includes parameters such as:

- **`name`**: The specific STT model to use.
- **`apiKey`**: Your API key for authentication.
- **Provider-specific options**: Additional options that may be required or supported by the specific voice provider.

**Note**: All of these parameters are optional. You can use the default settings provided by the voice provider, which will depend on the specific provider you are using.

```typescript
const voice = new OpenAIVoice({
  listeningModel: {
    name: 'whisper-1',
    apiKey: process.env.OPENAI_API_KEY,
  },
})

// If using default settings the configuration can be simplified to:
const voice = new OpenAIVoice()
```

## Available providers

Mastra supports several Speech-to-Text providers, each with their own capabilities and strengths:

- [**OpenAI**](https://mastra.ai/reference/voice/openai): High-accuracy transcription with Whisper models
- [**Azure**](https://mastra.ai/reference/voice/azure): Microsoft's speech recognition with enterprise-grade reliability
- [**ElevenLabs**](https://mastra.ai/reference/voice/elevenlabs): Advanced speech recognition with support for multiple languages
- [**Google**](https://mastra.ai/reference/voice/google): Google's speech recognition with extensive language support
- [**Cloudflare**](https://mastra.ai/reference/voice/cloudflare): Edge-optimized speech recognition for low-latency applications
- [**Deepgram**](https://mastra.ai/reference/voice/deepgram): AI-powered speech recognition with high accuracy for various accents
- [**Sarvam**](https://mastra.ai/reference/voice/sarvam): Specialized in Indic languages and accents

Each provider is implemented as a separate package that you can install as needed:

```bash
pnpm add @mastra/voice-openai@latest  # Example for OpenAI
```

## Using the listen method

The primary method for STT is the `listen()` method, which converts spoken audio into text. Here's how to use it:

```typescript
import { Agent } from '@mastra/core/agent'
import { OpenAIVoice } from '@mastra/voice-openai'
import { getMicrophoneStream } from '@mastra/node-audio'

const voice = new OpenAIVoice()

const agent = new Agent({
  id: 'voice-agent',
  name: 'Voice Agent',
  instructions: 'You are a voice assistant that provides recommendations based on user input.',
  model: 'openai/gpt-5.4',
  voice,
})

const audioStream = getMicrophoneStream() // Assume this function gets audio input

const transcript = await agent.voice.listen(audioStream, {
  filetype: 'm4a', // Optional: specify the audio file type
})

console.log(`User said: ${transcript}`)

const { text } = await agent.generate(
  `Based on what the user said, provide them a recommendation: ${transcript}`,
)

console.log(`Recommendation: ${text}`)
```

Check out the [Adding Voice to Agents](https://mastra.ai/docs/agents/adding-voice) documentation to learn how to use STT in an agent.