Speech-to-Text vs Text-to-Speech: Complete Guide

Voice AI involves two key technologies: Speech-to-Text (STT) and Text-to-Speech (TTS). Here's everything you need to know.

The Two Sides of Voice AI

Speech-to-Text (STT)

Converts spoken audio into written text.

• Also called: Transcription, ASR (Automatic Speech Recognition)
• Use cases: Voice commands, meeting notes, captions

Text-to-Speech (TTS)

Converts written text into spoken audio.

• Also called: Voice synthesis, speech synthesis
• Use cases: Audiobooks, voice assistants, accessibility

How They Work Together

User Speech → [STT] → Text → AI Processing → Text → [TTS] → Audio Response

Comparison Table

Feature	Speech-to-Text	Text-to-Speech
Input	Audio	Text
Output	Text	Audio
Example	Whisper, Google STT	LangVoice, ElevenLabs
Complexity	Very high	High
Latency	Real-time possible	Near-instant

Building a Complete Voice Assistant

import whisper  # STT
from langvoice_sdk import LangVoiceClient  # TTS
from openai import OpenAI

# Step 1: Transcribe user speech
model = whisper.load_model("base")
result = model.transcribe("user_audio.mp3")
user_text = result["text"]

# Step 2: Process with AI
openai = OpenAI()
response = openai.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": user_text}]
)
ai_response = response.choices[0].message.content

# Step 3: Convert to speech
langvoice = LangVoiceClient(api_key="your-key")
audio = langvoice.generate(text=ai_response, voice="heart")
audio.save("response.mp3")

Best TTS Options in 2024

Provider	Quality	Price	Best For
LangVoice	⭐⭐⭐⭐⭐	Free tier	Developers, AI agents
ElevenLabs	⭐⭐⭐⭐⭐	Expensive	Voice cloning
Google TTS	⭐⭐⭐⭐	Pay-per-use	Enterprise
Azure TTS	⭐⭐⭐⭐	Pay-per-use	Enterprise

Conclusion

Understanding both STT and TTS is essential for building complete voice AI applications. LangVoice provides the TTS component with 28+ natural voices and easy API integration.