Echogarden

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

• Easy to install, run, and update
• Written in TypeScript, for the Node.js runtime
• Can be used either as a command-line utility, or imported as a standard npm package
• Runs on Windows (x64, ARM64), macOS (x64, ARM64) and Linux (x64, ARM64)
• Doesn't require Python, Docker, or other system-level dependencies
• Doesn't rely on essential platform-specific binaries. Engines are either written in pure TypeScript, ported via WebAssembly, or imported using the ONNX runtime
• Fully open-source (GPL v3)

Features

• Text-to-speech using high-quality Kokoro and VITS offline models for many languages and dialects, and 16 other offline and online engines, including cloud services by Google, Microsoft, Amazon, OpenAI and Elevenlabs
• Speech-to-text using a custom TypeScript/ONNX port of the OpenAI Whisper speech recognition architecture, whisper.cpp, 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 synchronizes spoken audio in one language, to a provided English-translated transcript, using the Whisper engine
• Speech-to-transcript-and-translation alignment synchronizes spoken audio in one language, to a translation in a variety of other languages, given both a transcript and its translation
• Text-to-text translation, translates text between various languages. Supports cloud-based Google Translate engine
• Language detection identifies the language of a given audio or text. Includes Whisper or Silero engines for spoken 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 built-in Adaptive Gate algorithm
• Speech denoising attenuates background noise from spoken audio. Includes the RNNoise and NSNet2 engines
• Source separation isolates voice from any music or background ambience. Includes 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 Kokoro, VITS and eSpeak-NG synthesis engines, includes enhancements to improve TTS pronunciation accuracy: adds text normalization (e.g. idiomatic date and currency pronunciation), English heteronym disambiguation (based on a simple rule-based model), various pronunciation corrections, and accepts user-provided pronunciation lexicons
• Internal package system that auto-downloads and installs voices, models and other resources, as needed

Installation

Ensure you have Node.js v18 or later installed (v22 or later is recommended).

then:

npm install -g echogarden@latest

Update

You can use npm-check-updates to check for a newer version:

npm install -g npm-check-updates
ncu -g echogarden

Then, if an updated version is available, use the command line ncu provides to make the update.

Using the command-line interface

A small sample of command lines:

echogarden speak "Hello World!"
echogarden speak-file story.txt --engine=kokoro
echogarden transcribe speech.mp3
echogarden translate-speech speech.webm subtitles.srt
echogarden align speech.opus transcript.txt
echogarden isolate speech.wav

See the command-line interface guide for more details on the operations supported, and the configuration options reference for a comprehensive list of all options supported.

Using the Node.js API

If you are a developer, you can also directly import the package as a dependency in your code. The API operations and options closely mirror the CLI.

Documentation and guides

• Quick guide to the command-line interface
• Options reference
• Full list of all available engines
• Node.js API reference
• Enabling the CUDA ONNX execution provider
• 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.