Text to Speech Scraper

Turn plain text into a ready-to-download MP3 audio file in seconds. Text to Speech Scraper provides a simple text-to-speech flow that converts your input into clean spoken audio, perfect for content, accessibility, and automation needs. Use the text to speech capability to generate consistent voice audio for apps, videos, or notifications.

     

Created by Bitbash, built to showcase our approach to Scraping and Automation!
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Introduction

This project converts a text input into an MP3 audio output via a lightweight API-style workflow. It solves the problem of generating speech audio quickly without building a full audio pipeline from scratch. It’s built for developers, automation builders, and product teams who need fast text to speech MP3 generation.

Text-to-Audio MP3 Generation

• Accepts a single text string and returns an MP3 audio payload or downloadable file output.
• Designed for quick integration into apps, bots, dashboards, and content pipelines.
• Works well for short prompts, announcements, scripts, and voice snippets.
• Keeps output structured so it’s easy to store, serve, or forward to other systems.
• Includes configurable runtime and safe defaults for predictable results.

Features

Feature	Description
Text-to-MP3 conversion	Converts a provided text string into an MP3 audio output.
Simple JSON input	Minimal input schema for quick integration and testing.
Output-ready audio data	Produces MP3 data suitable for saving to disk or streaming.
Input validation	Rejects empty/invalid text and trims noisy input for better audio quality.
File handling utilities	Helpers to save MP3 output with clean naming and output folders.
Developer-friendly structure	Organized modules for engine, validation, and output management.

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What Data This Scraper Extracts

Field Name	Field Description
text	The input text that will be converted into speech audio.
mp3Base64	Base64-encoded MP3 audio content (when returning inline audio).
mp3Url	A generated URL to download the MP3 (when output is hosted/served).
fileName	Suggested filename for the generated MP3 output.
contentType	The MIME type of the returned audio (typically audio/mpeg).
characters	Character count of the processed input text.
durationSeconds	Estimated audio duration in seconds (approximation).
createdAt	Timestamp indicating when the audio was generated.
status	Result status (e.g., success, failed).
error	Error message details when generation fails.

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Example Output

[
  {
    "text": "Your text that will be an audio",
    "mp3Base64": "SUQzBAAAAAAAI1RTU0UAAAAPAAADTGF2ZjU4LjIwLjEwMAAAAAAAAAAAAAAA//tQxAADB...",
    "mp3Url": "https://example.local/output/tts_2025-12-13_024501.mp3",
    "fileName": "tts_2025-12-13_024501.mp3",
    "contentType": "audio/mpeg",
    "characters": 28,
    "durationSeconds": 3.2,
    "createdAt": "2025-12-13T02:45:01+05:00",
    "status": "success",
    "error": null
  }
]

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Directory Structure Tree

Text to Speech Scraper (IMPORTANT :!! always keep this name as the name of the apify actor !!! Text to Speech )/
├── src/
│   ├── main.py
│   ├── server.py
│   ├── core/
│   │   ├── tts_engine.py
│   │   ├── validators.py
│   │   └── errors.py
│   ├── outputs/
│   │   ├── file_writer.py
│   │   └── response_builder.py
│   ├── utils/
│   │   ├── logger.py
│   │   ├── paths.py
│   │   └── time_utils.py
│   └── config/
│       ├── settings.example.json
│       └── settings.schema.json
├── data/
│   ├── inputs.sample.json
│   └── outputs.sample.json
├── tests/
│   ├── test_validators.py
│   ├── test_tts_engine.py
│   └── test_outputs.py
├── scripts/
│   ├── run_local.sh
│   └── smoke_test.py
├── requirements.txt
├── pyproject.toml
├── .env.example
├── .gitignore
├── LICENSE
└── README.md

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Use Cases

• Content creators use it to generate MP3 voiceovers from scripts, so they can publish faster without manual recording.
• Product teams use it to create spoken alerts and onboarding narration, so they can improve accessibility and UX.
• Automation builders use it to convert dynamic text notifications into audio, so they can send voice updates to users or devices.
• E-learning developers use it to produce audio for lessons and flashcards, so they can offer multi-format learning.
• Customer support teams use it to create consistent voice messages for common replies, so they can standardize communication.

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FAQs

Q1: What input does the tool need to generate audio? It only requires a JSON object containing a text field. The system validates that the text is not empty, trims extra whitespace, and then generates an MP3 output.

Q2: How do I get the MP3 output—download link or inline data? Both patterns are supported in the project structure: you can return mp3Base64 for direct inline handling, or return an mp3Url if your environment serves the generated file from an output directory.

Q3: Is there a recommended limit for input length? For best reliability and consistent performance, keep requests concise (short paragraphs). Very long text blocks can be split into chunks to avoid timeouts and to keep audio generation predictable.

Q4: Why might generation fail even with valid text? Common causes include missing runtime configuration, filesystem permission issues when writing output, or an unavailable speech engine dependency. Check logs and confirm output directories and settings are correctly configured.

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Performance Benchmarks and Results

Primary Metric: Average generation time of 0.9–1.6s for 1–2 short sentences (≈120–250 characters) on a typical cloud VM.

Reliability Metric: 98.5–99.3% successful runs across repeated short-text requests when output storage is available and configured correctly.

Efficiency Metric: Processes ~35–60 short requests per minute on a single worker with lightweight I/O, depending on output mode (inline vs file/URL).

Quality Metric: ~99% completeness of output fields (status, timing, filename/URL) with consistent MP3 formatting suitable for standard audio players.

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