Google | Text to Speech.

  • Google
  • Text to Voice
  • $0.50–$10.00 per million tokens, depending on token type
  • ~10 sec average

Google Text to Speech converts your written text into natural-sounding speech.

View API docs

What Google | Text to Speech is good at.

  • Best for

    Developers building apps: Integrate Google | Text to Speech API for real-time voice feedback.

    Example prompt: " <speak>Welcome. Your balance is <break time="300ms"/> $150.</speak> " using Neural2 voice for natural app narration.

  • Limits and tips

    Getting good results

    Optimize prompts with SSML for precise control: use <break time="1s"/> for pauses, <prosody rate="slow" pitch="-2st"> for formal tones, enhancing natural flow…

  • Related model

    Mureka | Generate Track | Stem Generation

    Run it on the same input to compare output, speed and price.

    View model

Model documentation

About this model

Google Text to Speech converts your written text into natural-sounding speech. Simply type your text, choose a voice, and generate high-quality audio instantly.

Overview

Google | Text to Speech converts written text into natural-sounding speech using advanced AI models, solving the need for realistic audio in apps, content creation, and accessibility tools. Provided by Google as part of the google-tts family, it stands out with over 380 voices across 75+ languages, including premium Neural2 and WaveNet options for expressive, human-like output.

This Google text-to-voice solution powers everything from Google Docs read-aloud to enterprise APIs, delivering low-latency synthesis with customizable pitch, speed, and emotion via SSML markup. Developers appreciate its seamless REST/gRPC integration and continuous AI upgrades, making it ideal for real-time or batch audio generation on each::labs.

Whether building voice-enabled apps or enhancing e-learning, Google | Text to Speech ensures fluid, intelligible speech that engages global audiences without robotic tones.

Capabilities

  • Generates realistic speech with 380+ voices in 75+ languages using Neural2, WaveNet, and Studio models.
  • Customizes audio via SSML for pauses, emphasis, tone, emotion, and pronunciation control.
  • Supports multiple formats including MP3, WAV, OGG for web, telephony, or high-fidelity playback.
  • Offers adjustable parameters: speed (0.25-4x), pitch (±20 semitones), volume gain.
  • Enables custom voice training from studio audio for branded speech.
  • Provides synchronous/streaming synthesis for real-time apps or batch processing.
  • Integrates via REST/gRPC APIs with low-latency enterprise scalability.
  • Builds expressive, paced audio suitable for e-learning, IVR, and content creation.

Use cases

Developers building apps: Integrate Google | Text to Speech API for real-time voice feedback. Example prompt: "<speak>Welcome. Your balance is <break time="300ms"/> $150.</speak>" using Neural2 voice for natural app narration.

Content creators for e-learning: Generate multilingual lessons with WaveNet voices. Prompt: "<prosody rate="0.9">Photosynthesis converts light to energy.</prosody>" exports to MP3 for videos, leveraging 75+ language support.

Marketers for announcements: Create branded IVR or ads with custom pitch. Example: "<prosody pitch="-2st" volume="+3dB">Sale ends soon—shop now!</prosody>" in OGG for web streaming.

Accessibility designers: Power Google Docs read-aloud or Android hands-free with adjustable speed/pitch, ensuring inclusive experiences via each::labs deployment.

Tips & tricks

Optimize prompts with SSML for precise control: use <break time="1s"/> for pauses, <prosody rate="slow" pitch="-2st"> for formal tones, enhancing natural flow in Google | Text to Speech.

Select Neural2 voices like "en-US-Neural2-F" for female clarity or "en-US-Neural2-D" for dynamic range; adjust speaking_rate to 0.85 for announcements or 1.1 for upbeat notifications.

Example 1: "<speak>Please be advised <break time="500ms"/> that system maintenance begins at midnight.</speak>" yields a professional pause.

Example 2: "<prosody rate="1.1" pitch="+1st">Great news! Your order shipped.</prosody>" creates energetic delivery.

Example 3: Test sample rates at 24kHz for high-quality WAV exports. Integrate via each::labs for streamlined Google | Text to Speech API workflows, iterating with short texts first.

Technical spec

  • Voices: 380+ across 75+ languages and variants, including Standard, WaveNet, Neural2, and Studio tiers for varying quality levels.
  • Input: Plain text or SSML for pauses, pronunciation, tone, and emotion control.
  • Output Formats: MP3, WAV (LINEAR16), OGG_OPUS, MULAW, ALAW; sample rates up to 24kHz.
  • Customization: Speaking rate (0.25-4.0), pitch (-20 to +20 semitones), volume gain (-96 to +16 dB).
  • API Support: REST, gRPC; synchronous and streaming synthesis for real-time or batch use.
  • Processing: Low latency; handles enterprise-scale volumes with quick response times.
  • Custom Voices: Train models with studio-quality audio recordings.

Access via Google Cloud Text-to-Speech API on each::labs for high-fidelity audio output.

Things to be aware of

Google | Text to Speech may sound monotone in extended passages, especially Standard voices; opt for Neural2/Studio to mitigate.

Edge cases include complex SSML overuse causing synthesis errors—test incrementally. High-volume requests need quota monitoring to avoid throttling.

Common mistakes: Ignoring language codes leads to mismatched accents; always specify like "en-US-Neural2-F". Resource needs are low, but API calls require stable internet and authentication.

On Android/Docs, third-party engines can override defaults—verify Google Speech Recognition and Synthesis is active.

Key considerations

Before using Google | Text to Speech, ensure a Google Cloud account for API access, with free tiers available and paid pricing at $0.004–$0.016 per 1k characters—WaveNet/Neural2 voices cost more for superior quality.

Best for developer APIs, accessibility, and multilingual projects where integration with Google services matters; choose Standard voices for cost savings or Neural2/Studio for professional media.

Prerequisites include API keys and basic coding knowledge for Python/Node.js clients. Tradeoffs favor quality over emotion depth in long-form content compared to specialized TTS tools.

Limitations

Google | Text to Speech lacks deep emotional prosody in longer content, sounding less dynamic than specialized tools; Studio voices help but cost 10x more and support fewer languages.

No zero-shot voice cloning without custom training data. Character limits apply per request; batch long texts via streaming.

Telephony formats like MULAW suit narrowband but reduce quality. Free tier has usage caps; enterprise scale requires paid plans.

 

Questions about this model

The short answers. For anything specific to your setup, talk to our team.

Talk to an engineerPlan for your expected volume.
  • Google Text to Speech is a neural text-to-voice model developed by Google that converts written text into natural-sounding audio. It supports multiple languages, accents, and voice types including Standard and WaveNet voices, producing high-quality audio suitable for applications, notifications, and accessibility tools.

Ready to close the gap?

Find the model. Build the workflow. Ship the result.