echogarden

Echogarden

Echogarden is an easy-to-use speech toolset that includes a variety of speech processing tools.

• Easy to install, run, and update
• Runs on Windows (x64), macOS (x64, ARM64) and Linux (x64, ARM64)
• Written in TypeScript, for the Node.js runtime
• Doesn't require Python, Docker, or other system-level dependencies
• Doesn't rely on essential platform-specific binaries. Engines are either ported via WebAssembly, imported using the ONNX runtime, or written in pure JavaScript

Features

• Text-to-speech using the VITS neural architecture, and 15 other offline and online engines, including cloud services by Google, Microsoft, Amazon, OpenAI and Elevenlabs
• Speech-to-text using OpenAI Whisper, and several other engines, including cloud services by Google, Microsoft, Amazon and OpenAI
• Speech-to-transcript alignment using several variants of dynamic time warping (DTW, DTW-RA), including support for multi-pass (hierarchical) processing, or via guided decoding using Whisper recognition models. Supports 100+ languages
• Speech-to-text translation, translates speech in any of the 98 languages supported by Whisper, to English, with near word-level timing for the translated transcript
• Speech-to-translated-transcript alignment attempts to synchronize spoken audio in one language, to a provided English-translated transcript, using the Whisper engine
• Language detection identifies the language of a given audio or text. Provides Whisper or Silero engines for audio, and TinyLD or FastText for text
• Voice activity detection attempts to identify segments of audio where voice is active or inactive. Includes WebRTC VAD, Silero VAD, RNNoise-based VAD and a custom Adaptive Gate
• Speech denoising attenuates background noise from spoken audio. Includes the RNNoise engine
• Source separation isolates voice from any music or background ambience. Supports the MDX-NET deep learning architecture
• Word-level timestamps for all recognition, synthesis, alignment and translation outputs
• Advanced subtitle generation, accounting for sentence and phrase boundaries
• For the VITS and eSpeak-NG synthesis engines, includes enhancements to improve TTS pronunciation accuracy: adds text normalization (e.g. idiomatic date and currency pronunciation), heteronym disambiguation (based on a rule-based model) and user-customizable pronunciation lexicons
• Internal package system that auto-downloads and installs voices, models and other resources, as needed

Installation

Ensure you have Node.js v18.16.0 or later installed.

then:

npm install echogarden -g

Additional required tools:

• ffmpeg: used for codec conversions
• sox: used for the CLI's audio playback

Both tools are auto-downloaded as internal packages on Windows and Linux.

On macOS, only ffmpeg is currently auto-downloaded. It is recommended to install sox via a system package manager like Homebrew (brew install sox) to ensure it is available on the system path.

Updating to latest version

npm update echogarden -g

Using the toolset

Tools are accessible via a command-line interface, which enables powerful customization and is especially useful for long-running bulk operations.

Development of more graphical and interactive tooling is planned. A text-to-speech browser extension is currently under development (but not released yet).

If you are a developer, you can also import the package as a module or interface with it via a local WebSocket service (currently experimental).

Documentation

• Quick guide to the command-line interface
• Options reference
• Full list of supported engines
• Node.js API reference
• Technical overview and Q&A
• How to help
• Setting up a development environment
• Developer's task list
• Release notes (for releases up to 1.0.0)

Credits

This project consolidates, and builds upon the effort of many different individuals and companies, as well as contributing a number of original works.

Developed by Rotem Dan (IPA: /ˈʁɒːtem ˈdän/).

License

GNU General Public License v3

Licenses for components, models and other dependencies are detailed on this page.