Voice

Mastra agents can be enhanced with voice capabilities, allowing them to speak responses and listen to user input. You can configure an agent to use either a single voice provider or combine multiple providers for different operations.

Basic usage

The simplest way to add voice to an agent is to use a single provider for both speaking and listening:

import { createReadStream } from 'fs'
import path from 'path'
import { Agent } from '@mastra/core/agent'
import { OpenAIVoice } from '@mastra/voice-openai'

// Initialize the voice provider with default settings
const voice = new OpenAIVoice()

// Create an agent with voice capabilities
export const agent = new Agent({
  id: 'voice-agent',
  name: 'Voice Agent',
  instructions: `You are a helpful assistant with both STT and TTS capabilities.`,
  model: 'openai/gpt-5.1',
  voice,
})

// The agent can now use voice for interaction
const audioStream = await agent.voice.speak("Hello, I'm your AI assistant!", {
  filetype: 'm4a',
})

playAudio(audioStream!)

try {
  const transcription = await agent.voice.listen(audioStream)
  console.log(transcription)
} catch (error) {
  console.error('Error transcribing audio:', error)
}

Working with Audio Streams

The speak() and listen() methods work with Node.js streams. Here's how to save and load audio files:

Saving Speech Output

The speak method returns a stream that you can pipe to a file or speaker.

import { createWriteStream } from 'fs'
import path from 'path'

// Generate speech and save to file
const audio = await agent.voice.speak('Hello, World!')
const filePath = path.join(process.cwd(), 'agent.mp3')
const writer = createWriteStream(filePath)

audio.pipe(writer)

await new Promise<void>((resolve, reject) => {
  writer.on('finish', () => resolve())
  writer.on('error', reject)
})

Transcribing Audio Input

The listen method expects a stream of audio data from a microphone or file.

import { createReadStream } from 'fs'
import path from 'path'

// Read audio file and transcribe
const audioFilePath = path.join(process.cwd(), '/agent.m4a')
const audioStream = createReadStream(audioFilePath)

try {
  console.log('Transcribing audio file...')
  const transcription = await agent.voice.listen(audioStream, {
    filetype: 'm4a',
  })
  console.log('Transcription:', transcription)
} catch (error) {
  console.error('Error transcribing audio:', error)
}

Speech-to-Speech Voice Interactions

For more dynamic and interactive voice experiences, you can use real-time voice providers that support speech-to-speech capabilities:

import { Agent } from '@mastra/core/agent'
import { getMicrophoneStream } from '@mastra/node-audio'
import { OpenAIRealtimeVoice } from '@mastra/voice-openai-realtime'
import { search, calculate } from '../tools'

// Initialize the realtime voice provider
const voice = new OpenAIRealtimeVoice({
  apiKey: process.env.OPENAI_API_KEY,
  model: 'gpt-5.1-realtime',
  speaker: 'alloy',
})

// Create an agent with speech-to-speech voice capabilities
export const agent = new Agent({
  id: 'speech-to-speech-agent',
  name: 'Speech-to-Speech Agent',
  instructions: `You are a helpful assistant with speech-to-speech capabilities.`,
  model: 'openai/gpt-5.1',
  tools: {
    // Tools configured on Agent are passed to voice provider
    search,
    calculate,
  },
  voice,
})

// Establish a WebSocket connection
await agent.voice.connect()

// Start a conversation
agent.voice.speak("Hello, I'm your AI assistant!")

// Stream audio from a microphone
const microphoneStream = getMicrophoneStream()
agent.voice.send(microphoneStream)

// When done with the conversation
agent.voice.close()

Event System

The realtime voice provider emits several events you can listen for:

// Listen for speech audio data sent from voice provider
agent.voice.on('speaking', ({ audio }) => {
  // audio contains ReadableStream or Int16Array audio data
})

// Listen for transcribed text sent from both voice provider and user
agent.voice.on('writing', ({ text, role }) => {
  console.log(`${role} said: ${text}`)
})

// Listen for errors
agent.voice.on('error', error => {
  console.error('Voice error:', error)
})

Examples

End-to-end voice interaction

This example demonstrates a voice interaction between two agents. The hybrid voice agent, which uses multiple providers, speaks a question, which is saved as an audio file. The unified voice agent listens to that file, processes the question, generates a response, and speaks it back. Both audio outputs are saved to the audio directory.

The following files are created:

• hybrid-question.mp3 – Hybrid agent's spoken question.
• unified-response.mp3 – Unified agent's spoken response.

src/test-voice-agents.ts

import 'dotenv/config'

import path from 'path'
import { createReadStream } from 'fs'
import { Agent } from '@mastra/core/agent'
import { CompositeVoice } from '@mastra/core/voice'
import { OpenAIVoice } from '@mastra/voice-openai'
import { Mastra } from '@mastra/core'

// Saves an audio stream to a file in the audio directory, creating the directory if it doesn't exist.
export const saveAudioToFile = async (
  audio: NodeJS.ReadableStream,
  filename: string,
): Promise<void> => {
  const audioDir = path.join(process.cwd(), 'audio')
  const filePath = path.join(audioDir, filename)

  await fs.promises.mkdir(audioDir, { recursive: true })

  const writer = createWriteStream(filePath)
  audio.pipe(writer)
  return new Promise((resolve, reject) => {
    writer.on('finish', resolve)
    writer.on('error', reject)
  })
}

// Saves an audio stream to a file in the audio directory, creating the directory if it doesn't exist.
export const convertToText = async (input: string | NodeJS.ReadableStream): Promise<string> => {
  if (typeof input === 'string') {
    return input
  }

  const chunks: Buffer[] = []
  return new Promise((resolve, reject) => {
    inputData.on('data', chunk => chunks.push(Buffer.from(chunk)))
    inputData.on('error', reject)
    inputData.on('end', () => resolve(Buffer.concat(chunks).toString('utf-8')))
  })
}

export const hybridVoiceAgent = new Agent({
  id: 'hybrid-voice-agent',
  name: 'Hybrid Voice Agent',
  model: 'openai/gpt-5.1',
  instructions: 'You can speak and listen using different providers.',
  voice: new CompositeVoice({
    input: new OpenAIVoice(),
    output: new OpenAIVoice(),
  }),
})

export const unifiedVoiceAgent = new Agent({
  id: 'unified-voice-agent',
  name: 'Unified Voice Agent',
  instructions: 'You are an agent with both STT and TTS capabilities.',
  model: 'openai/gpt-5.1',
  voice: new OpenAIVoice(),
})

export const mastra = new Mastra({
  agents: { hybridVoiceAgent, unifiedVoiceAgent },
})

const hybridVoiceAgent = mastra.getAgent('hybridVoiceAgent')
const unifiedVoiceAgent = mastra.getAgent('unifiedVoiceAgent')

const question = 'What is the meaning of life in one sentence?'

const hybridSpoken = await hybridVoiceAgent.voice.speak(question)

await saveAudioToFile(hybridSpoken!, 'hybrid-question.mp3')

const audioStream = createReadStream(path.join(process.cwd(), 'audio', 'hybrid-question.mp3'))
const unifiedHeard = await unifiedVoiceAgent.voice.listen(audioStream)

const inputText = await convertToText(unifiedHeard!)

const unifiedResponse = await unifiedVoiceAgent.generate(inputText)
const unifiedSpoken = await unifiedVoiceAgent.voice.speak(unifiedResponse.text)

await saveAudioToFile(unifiedSpoken!, 'unified-response.mp3')

Using Multiple Providers

For more flexibility, you can use different providers for speaking and listening using the CompositeVoice class:

import { Agent } from '@mastra/core/agent'
import { CompositeVoice } from '@mastra/core/voice'
import { OpenAIVoice } from '@mastra/voice-openai'
import { PlayAIVoice } from '@mastra/voice-playai'

export const agent = new Agent({
  id: 'voice-agent',
  name: 'Voice Agent',
  instructions: `You are a helpful assistant with both STT and TTS capabilities.`,
  model: 'openai/gpt-5.1',

  // Create a composite voice using OpenAI for listening and PlayAI for speaking
  voice: new CompositeVoice({
    input: new OpenAIVoice(),
    output: new PlayAIVoice(),
  }),
})

Using AI SDK

Mastra supports using AI SDK's transcription and speech models directly in CompositeVoice, giving you access to a wide range of providers through the AI SDK ecosystem:

import { Agent } from '@mastra/core/agent'
import { CompositeVoice } from '@mastra/core/voice'
import { openai } from '@ai-sdk/openai'
import { elevenlabs } from '@ai-sdk/elevenlabs'
import { groq } from '@ai-sdk/groq'

export const agent = new Agent({
  id: 'aisdk-voice-agent',
  name: 'AI SDK Voice Agent',
  instructions: `You are a helpful assistant with voice capabilities.`,
  model: 'openai/gpt-5.1',

  // Pass AI SDK models directly to CompositeVoice
  voice: new CompositeVoice({
    input: openai.transcription('whisper-1'), // AI SDK transcription model
    output: elevenlabs.speech('eleven_turbo_v2'), // AI SDK speech model
  }),
})

// Use voice capabilities as usual
const audioStream = await agent.voice.speak('Hello!')
const transcribedText = await agent.voice.listen(audioStream)

Mix and Match Providers

You can mix AI SDK models with Mastra voice providers:

import { CompositeVoice } from '@mastra/core/voice'
import { PlayAIVoice } from '@mastra/voice-playai'
import { openai } from '@ai-sdk/openai'

// Use AI SDK for transcription and Mastra provider for speech
const voice = new CompositeVoice({
  input: openai.transcription('whisper-1'), // AI SDK
  output: new PlayAIVoice(), // Mastra provider
})

For the complete list of supported AI SDK providers and their capabilities:

• Transcription
• Speech

Supported Voice Providers

Mastra supports multiple voice providers for text-to-speech (TTS) and speech-to-text (STT) capabilities:

Provider	Package	Features	Reference
OpenAI	@mastra/voice-openai	TTS, STT	Documentation
OpenAI Realtime	@mastra/voice-openai-realtime	Realtime speech-to-speech	Documentation
ElevenLabs	@mastra/voice-elevenlabs	High-quality TTS	Documentation
PlayAI	@mastra/voice-playai	TTS	Documentation
Google	@mastra/voice-google	TTS, STT	Documentation
Deepgram	@mastra/voice-deepgram	STT	Documentation
Murf	@mastra/voice-murf	TTS	Documentation
Speechify	@mastra/voice-speechify	TTS	Documentation
Sarvam	@mastra/voice-sarvam	TTS, STT	Documentation
Azure	@mastra/voice-azure	TTS, STT	Documentation
Cloudflare	@mastra/voice-cloudflare	TTS	Documentation

Next Steps

• Voice API Reference - Detailed API documentation for voice capabilities
• Text to Speech Examples - Interactive story generator and other TTS implementations
• Speech to Text Examples - Voice memo app and other STT implementations
• Speech to Speech Examples - Real-time voice conversation with call analysis