# Gtts

> Google Text-to-Speech (gTTS) for converting text to audio. Use when creating audiobooks, podcasts, or speech synthesis from text. Handles long text by chunking at sentence boundaries and concatenating audio segments with pydub. Use when this capability is needed.

- Skill: `tomevault-io/gtts` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add tomevault-io/gtts`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/gtts/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: tomevault-io (https://skillmd.com/u/tomevault-io)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tomevault-io/gtts

---


# Google Text-to-Speech (gTTS)

gTTS is a Python library that converts text to speech using Google's Text-to-Speech API. It's free to use and doesn't require an API key.

## Installation

```bash
pip install gtts pydub
```

pydub is useful for manipulating and concatenating audio files.

## Basic Usage

```python
from gtts import gTTS

# Create speech
tts = gTTS(text="Hello, world!", lang='en')

# Save to file
tts.save("output.mp3")
```

## Language Options

```python
# US English (default)
tts = gTTS(text="Hello", lang='en')

# British English
tts = gTTS(text="Hello", lang='en', tld='co.uk')

# Slow speech
tts = gTTS(text="Hello", lang='en', slow=True)
```

## Python Example for Long Text

```python
from gtts import gTTS
from pydub import AudioSegment
import tempfile
import os
import re

def chunk_text(text, max_chars=4500):
    """Split text into chunks at sentence boundaries."""
    sentences = re.split(r'(?<=[.!?])\s+', text)
    chunks = []
    current_chunk = ""

    for sentence in sentences:
        if len(current_chunk) + len(sentence) < max_chars:
            current_chunk += sentence + " "
        else:
            if current_chunk:
                chunks.append(current_chunk.strip())
            current_chunk = sentence + " "

    if current_chunk:
        chunks.append(current_chunk.strip())

    return chunks


def text_to_audiobook(text, output_path):
    """Convert long text to a single audio file."""
    chunks = chunk_text(text)
    audio_segments = []

    for i, chunk in enumerate(chunks):
        # Create temp file for this chunk
        with tempfile.NamedTemporaryFile(suffix='.mp3', delete=False) as tmp:
            tmp_path = tmp.name

        # Generate speech
        tts = gTTS(text=chunk, lang='en', slow=False)
        tts.save(tmp_path)

        # Load and append
        segment = AudioSegment.from_mp3(tmp_path)
        audio_segments.append(segment)

        # Cleanup
        os.unlink(tmp_path)

    # Concatenate all segments
    combined = audio_segments[0]
    for segment in audio_segments[1:]:
        combined += segment

    # Export
    combined.export(output_path, format="mp3")
```

## Handling Large Documents

gTTS has a character limit per request (~5000 chars). For long documents:

1. Split text into chunks at sentence boundaries
2. Generate audio for each chunk using gTTS
3. Use pydub to concatenate the chunks

## Alternative: Using ffmpeg for Concatenation

If you prefer ffmpeg over pydub:

```bash
# Create file list
echo "file 'chunk1.mp3'" > files.txt
echo "file 'chunk2.mp3'" >> files.txt

# Concatenate
ffmpeg -f concat -safe 0 -i files.txt -c copy output.mp3
```

## Best Practices

- Split at sentence boundaries to avoid cutting words mid-sentence
- Use `slow=False` for natural speech speed
- Handle network errors gracefully (gTTS requires internet)
- Consider adding brief pauses between chapters/sections

## Limitations

- Requires internet connection (uses Google's servers)
- Voice quality is good but not as natural as paid services
- Limited voice customization options
- May have rate limits for very heavy usage

---
> Converted and distributed by [TomeVault](https://tomevault.io/claim/benchflow-ai) — claim your Tome and manage your conversions.
<!-- tomevault:4.0:skill_md:2026-04-11 -->