Gemini Tts

Gemini Text-to-Speech

Generate natural-sounding speech from text using Gemini's TTS models through executable scripts with support for multiple voices and multi-speaker conversations.

When to Use This Skill

Use this skill when you need to:

• Convert text to natural speech
• Create audio for podcasts, audiobooks, or videos
• Generate multi-speaker conversations
• Stream audio for long content
• Choose from multiple voice options
• Create accessible audio content
• Generate voiceovers for presentations
• Batch convert text to audio files

Available Scripts

scripts/tts.py

Purpose: Convert text to speech using Gemini TTS models

When to use:

• Any text-to-speech conversion
• Multi-speaker conversation generation
• Streaming audio for long texts
• Voiceovers for content creation
• Accessible audio generation

Key parameters:

Output: WAV audio file path

Workflows

Workflow 1: Basic Text-to-Speech

python scripts/tts.py "Hello, world! Have a wonderful day."

• Best for: Quick audio generation, simple messages
• Voice: Kore (default, clear and professional)
• Output: audio/tts_output_YYYYMMDD_HHMMSS.wav (auto timestamp)

Workflow 2: Choose Different Voice

python scripts/tts.py "Welcome to our podcast about technology trends" --voice Puck --output welcome

• Best for: Friendly, conversational content
• Voice options: Kore, Puck, Charon, Fenrir, Aoede, Zephyr, Sulafat
• Output: audio/welcome_YYYYMMDD_HHMMSS.wav

Workflow 3: Multi-Speaker Conversation

python scripts/tts.py "TTS the following conversation:
Joe: How's it going today?
Jane: Not too bad, how about you?
Joe: I'm working on a new project.
Jane: Sounds exciting, tell me more!" --speakers "Joe:Kore,Jane:Puck" --output conversation

• Best for: Dialogues, interviews, role-playing content
• Format: Marked conversation with speaker names
• Script automatically routes text to appropriate voices
• Output: audio/conversation_YYYYMMDD_HHMMSS.wav

Workflow 4: Long Content with Streaming

python scripts/tts.py "This is a very long text that would benefit from streaming..." --stream --output long-form

• Best for: Podcasts, audiobooks, long articles
• Streaming: Processes audio in chunks for long texts
• Output: audio/long-form_YYYYMMDD_HHMMSS.wav

Workflow 5: Professional Voiceover

python scripts/tts.py "Welcome to our quarterly earnings presentation. Today we'll discuss our growth metrics and future plans." --voice Charon --output voiceover

• Best for: Corporate content, presentations, formal announcements
• Voice: Charon (deep, authoritative)
• Use when: Professional, serious tone required

Workflow 6: Custom Output Directory

python scripts/tts.py "Save to specific folder." --output-dir ./my-projects/podcasts/ --output episode1

• Best for: Organized project structures
• Directory created automatically if it doesn't exist
• Output: ./my-projects/podcasts/episode1_YYYYMMDD_HHMMSS.wav

Workflow 7: Content Creation Pipeline (Text → Audio)

# 1. Generate script (gemini-text skill)
python skills/gemini-text/scripts/generate.py "Write a 2-minute podcast intro about sustainable energy"

# 2. Generate audio (this skill)
python scripts/tts.py "[Paste generated script]" --voice Fenrir --output podcast-intro

# 3. Use in video or podcast

• Best for: Podcasts, audiobooks, video narration
• Combines with: gemini-text for script generation

Workflow 8: Accessible Content

python scripts/tts.py "Welcome to our accessible website. This audio describes our main navigation options." --voice Aoede --output accessibility

• Best for: Web accessibility, screen reader alternatives
• Voice: Aoede (melodic, pleasant)
• Use when: Making content accessible to visually impaired users

Workflow 9: Educational Content

python scripts/tts.py "Chapter 1: Introduction to Quantum Computing. Let's explore the fundamental principles..." --voice Zephyr --output chapter1

• Best for: Educational materials, tutorials, e-learning
• Voice: Zephyr (light, airy)
• Combines well with: gemini-text for content generation

Workflow 10: Disable Timestamp

python scripts/tts.py "Fixed filename." --output my-audio --no-timestamp

• Best for: When you want complete control over filename
• Output: audio/my-audio.wav (no timestamp)
• Use when: Generating files for specific naming schemes

Parameters Reference

Model Selection

Voice Selection

Audio Format

Token Limits

Output Interpretation

Audio File

• Format: WAV (compatible with most players)
• Mono channel (single audio track)
• Sample rate: 24000 Hz (broadcast quality)
• Can be converted to MP3/AAC if needed

Multi-Speaker Files

• Single WAV file with multiple voices
• Voices separated by timing within file
• Use --speakers parameter to map speakers to voices

Streaming Output

• Audio processed in chunks during generation
• Script shows "Streaming audio..." message
• Useful for very long texts or real-time applications

Common Issues

"google-genai not installed"

pip install google-genai

"Voice name not found"

• Check voice name spelling
• Use available voices: Kore, Puck, Charon, Fenrir, Aoede, Zephyr, Sulafat
• Voice names are case-sensitive

"No audio generated"

• Check text is not empty
• Verify text doesn't exceed token limit (8,192)
• Try shorter text segments
• Check API quota limits

"Multi-speaker format error"

• Format: SpeakerName:VoiceName,Speaker2:Voice2
• Separate speakers with commas
• Use colon between speaker and voice
• Example: "Joe:Kore,Jane:Puck,Host:Charon"

"Output file already exists"

• Script will overwrite existing files
• Change --output filename to avoid conflicts
• Use unique names for batch generation

Audio quality issues

• Check input text for unusual characters
• Try different voice for better pronunciation
• Consider splitting long text into smaller segments
• Verify audio playback software compatibility

Best Practices

Voice Selection

• Kore: General purpose, clear articulation
• Puck: Conversational, engaging tone
• Charon: Professional, authoritative
• Fenrir: Emotional, storytelling
• Aoede: Soft, gentle for accessibility
• Zephyr: Educational, clear explanations

Text Preparation

• Use natural language and punctuation
• Include pauses with commas and periods
• Spell out difficult words if needed
• Break very long text into logical segments
• Add speaker labels for multi-speaker content

Performance Optimization

• Use streaming for very long texts
• Generate shorter segments for better control
• Use flash model for faster generation
• Batch process multiple files for efficiency

Quality Tips

• Test different voices for your content type
• Use appropriate pacing with punctuation
• Consider context when selecting voice
• Listen to output before final use
• Multi-speaker requires clear speaker labeling

Use Cases by Voice

Related Skills

• gemini-text: Generate scripts and text for TTS
• gemini-image: Create visuals to accompany audio
• gemini-batch: Process multiple TTS requests efficiently
• gemini-files: Upload audio files for processing

Quick Reference

# Basic
python scripts/tts.py "Your text here"

# Custom voice
python scripts/tts.py "Your text" --voice Puck --output audio.wav

# Multi-speaker
python scripts/tts.py "Joe: Hi. Jane: Hello!" --speakers "Joe:Kore,Jane:Puck"

# Streaming
python scripts/tts.py "Long text..." --stream --output long.wav

# Professional
python scripts/tts.py "Corporate announcement" --voice Charon

Reference

• See references/voices.md for complete voice documentation
• Get API key: https://aistudio.google.com/apikey
• Documentation: https://ai.google.dev/gemini-api/docs/text-to-speech
• Sample rate: 24000 Hz standard for most applications