easy-edge-tts 0.1.0

High-level TTS with voice rotation and mood selection for content creators

Voice Forge 🎙️

High-level TTS with voice rotation and mood selection for content creators

Voice Forge makes text-to-speech dead simple. Built on top of Edge TTS (free, high-quality Microsoft voices), it adds voice rotation, mood-based selection, and word-level timestamps - everything content creators need.

✨ Features

• 🆓 Free - Uses Microsoft Edge TTS (no API key needed)
• 🎭 20+ voices - Male, female, US, UK, Australian accents
• 🎯 Mood-based selection - Pick voices that match your content
• 🔄 Voice rotation - Automatic variety across multiple generations
• ⏱️ Word timestamps - Perfect for synchronized subtitles
• 🚀 Async-first - Built for modern Python

📦 Installation

pip install voice-forge

For ElevenLabs support (premium voices):

pip install voice-forge[elevenlabs]

🚀 Quick Start

Simple One-Liner

from voice_forge import speak

await speak("Hello world!", "output.mp3")

Choose a Voice

from voice_forge import EdgeTTS

# Use a specific voice
tts = EdgeTTS(voice="aria")  # Expressive, dramatic female
result = await tts.generate("The tension was unbearable...", "drama.mp3")

print(f"Generated {result.duration:.1f}s of audio")

Mood-Based Selection

from voice_forge import VoiceRotator

rotator = VoiceRotator()

# Get a voice that matches the mood
tts = rotator.get_tts_for_mood("dramatic")
await tts.generate("And then... everything changed.", "scene.mp3")

# Available moods: dramatic, suspense, scary, happy, sad, news, tutorial, podcast, aita, revenge, heartwarming, shocking

Voice Rotation for Variety

from voice_forge import VoiceRotator

rotator = VoiceRotator()

stories = ["Story one...", "Story two...", "Story three..."]

for i, story in enumerate(stories):
    # Each story gets a different voice
    tts = rotator.get_next_tts()
    await tts.generate(story, f"story_{i}.mp3")

Word-Level Timestamps (for subtitles)

from voice_forge import EdgeTTS

tts = EdgeTTS(voice="guy")
result, timestamps = await tts.generate_with_timestamps(
    "This is perfect for creating synchronized subtitles.",
    "output.mp3"
)

for word in timestamps:
    print(f"{word['start']:.2f}s - {word['end']:.2f}s: {word['text']}")

🎭 Available Voices

Name	Gender	Accent	Best For
guy	Male	US	Storytelling, warm narratives
jenny	Female	US	Friendly, versatile content
aria	Female	US	Dramatic, emotional content
davis	Male	US	Professional, authoritative
ryan	Male	UK	British, formal content
sonia	Female	UK	British, warm professional
thomas	Male	UK	Deep, serious, dramatic

See all 20+ voices →

🎯 Mood Categories

Perfect for content creators who need the right voice for their content:

Mood	Best Voices	Use Case
dramatic	aria, guy, ryan	Reddit stories, drama
suspense	aria, thomas, davis	Thriller content
happy	jenny, sara, tony	Upbeat content
news	davis, nancy, ryan	News, reports
aita	guy, aria, jenny	"Am I The A-hole" stories
tutorial	jenny, guy, sara	How-to videos

🎚️ Adjust Speed and Pitch

from voice_forge import EdgeTTS

tts = EdgeTTS(voice="guy")

# Faster for short-form content
await tts.generate("Quick update!", "fast.mp3", rate="+20%")

# Slower for dramatic effect
await tts.generate("And then...", "slow.mp3", rate="-30%")

# Higher pitch
await tts.generate("Exciting news!", "high.mp3", pitch="+10Hz")

💎 ElevenLabs (Premium)

For the most natural-sounding voices:

from voice_forge import ElevenLabsTTS

tts = ElevenLabsTTS(
    api_key="your-api-key",
    voice_id="your-voice-id"
)

result = await tts.generate("Premium quality voice.", "premium.mp3")

📋 Requirements

• Python 3.10+
• ffprobe (optional, for accurate duration detection)

# Ubuntu/Debian
sudo apt install ffmpeg

# macOS
brew install ffmpeg

# Windows
# Download from https://ffmpeg.org/download.html

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📄 License

MIT License - feel free to use in your projects!

---

Made with ❤️ for content creators