How do I integrate speech-to-text and text-to-speech APIs into my app?

Integrating speech-to-text (STT) and text-to-speech (TTS) usually looks like this:

1) Choose providers

Common options:

• Cloud APIs: Google Cloud Speech/TTS, AWS Transcribe/Polly, Azure Speech
• Device/browser APIs: Web Speech API (limited support/quality)
• Open-source/local: Whisper for STT, Coqui TTS, Piper, etc.

Pick based on:

• language support
• latency
• streaming vs batch
• cost
• privacy/offline needs

2) Typical app architecture

A simple flow is:

1. User speaks
2. App records audio from mic
3. Send audio to STT API
4. Receive text transcript
5. Process transcript in your app
6. Generate response text
7. Send text to TTS API
8. Play returned audio

For real-time voice apps, use streaming STT and streaming TTS if available.

3) Frontend: capture audio

In a web app, you can capture microphone input with:

• navigator.mediaDevices.getUserMedia()
• MediaRecorder for short audio chunks

For mobile:

• iOS: AVAudioRecorder / AVAudioEngine
• Android: AudioRecord / MediaRecorder
• Cross-platform: React Native / Flutter plugins

4) Backend: send audio to STT

Usually your backend should:

• receive uploaded audio
• authenticate with the STT provider
• send audio in the required format
• return transcript to the frontend

Why backend?

• protects API keys
• handles file conversion
• centralizes rate limiting/logging

5) Generate speech with TTS

After getting your response text:

• send text to TTS API
• receive MP3/WAV/OGG audio
• stream or return the audio URL/file
• play it in the app

6) Handle audio formats

APIs often require specific formats:

• WAV (16 kHz mono PCM) is commonly accepted for STT
• MP3 or OGG is common for TTS output

You may need to:

• convert codecs
• resample audio
• normalize channels/sample rates

7) Add error handling

Plan for:

• no microphone permission
• low network connectivity
• partial/incorrect transcripts
• unsupported audio format
• API timeouts / quota limits

8) Security and privacy

• keep API keys on the server
• tell users when recording starts
• store audio/transcripts only if needed
• comply with privacy laws if applicable

9) Example flow in code terms

Pseudo-logic:

// 1. Capture audio
const audioBlob = await recordFromMic();

// 2. Send to STT
const transcript = await fetch('/api/stt', {
  method: 'POST',
  body: audioBlob
}).then(r => r.json());

// 3. Process transcript
const replyText = await getReply(transcript.text);

// 4. Send to TTS
const speechAudio = await fetch('/api/tts', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({ text: replyText })
}).then(r => r.blob());

// 5. Play audio
playAudio(speechAudio);

10) If you want real-time conversation

Use:

• WebSockets or streaming APIs
• chunked audio upload
• partial transcripts
• low-latency playback

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If you want, I can give you:

1. a working example in JavaScript, Python, or React Native
2. a guide using a specific provider like OpenAI, Google, AWS, or Azure
3. a full end-to-end architecture for a voice assistant app