{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/14"},{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/16"},{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/8"},{"label":"Multimedia","url":"https://skillfed.io/packages/category/multimedia"},{"label":"Sound/Audio","url":"https://skillfed.io/packages/category/multimedia-sound-audio"},{"label":"Speech","url":"https://skillfed.io/packages/category/multimedia-sound-audio-speech"}],"enrichment":{"capability":"Coqui TTS synthesizes speech from text using deep learning models, supporting over 1100 languages with pretrained weights and tools for training and fine-tuning custom models.","skillfed_tags":["speech-synthesis","voice-conversion","multilingual"],"use_cases":["Generate speech from text in multiple languages using pretrained models without training","Fine-tune an existing TTS model on your own voice or dataset to customize output","Build a voice cloning system that generates speech in a target speaker's voice from a short audio sample","Convert one speaker's voice to another while preserving the linguistic content","Train a multilingual or multi-speaker TTS model from scratch on custom data","Analyze and curate TTS training datasets using built-in dataset analysis tools"],"what_it_does":"Coqui TTS is a deep learning library for converting text into natural-sounding speech. It bundles multiple neural architectures (Tacotron2, Glow-TTS, VITS, XTTS, and others) with pretrained weights across many languages, plus vocoders to convert spectrograms to audio. You can use it off-the-shelf for inference, fine-tune existing models on your own data, or train new models from scratch. It also supports voice conversion (changing a speaker's identity while preserving content) and voice cloning with minimal reference audio.\n\nThe library is designed for both research and production use. It provides command-line tools and a Python API, with utilities for dataset curation and analysis. The main constraint is that external PyTorch installation is required, and the full dependency stack (transformers, librosa, scipy, numba, and others) is substantial. Training new models is computationally expensive; inference can run on CPU but is much faster on GPU.","worth_installing":"Yes, if you need multilingual text-to-speech synthesis or voice conversion. The library is actively maintained, has no known vulnerabilities, and offers both easy inference and advanced training capabilities. Install it if you want pretrained models out-of-the-box or plan to fine-tune. The MPL-2.0 copyleft license is permissive for unmodified use in closed-source work but requires sharing modifications. Be aware that external PyTorch installation is required and the dependency footprint is large."},"id":"coqui-tts","links":{"html":"https://skillfed.io/packages/coqui-tts","md":"https://skillfed.io/packages/coqui-tts.md","pypi":"https://pypi.org/project/coqui-tts/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-01-26","license_spdx":null,"license_treatment":"copyleft","name":"coqui-tts","python_support":"supports_current","summary":"Deep learning for Text to Speech."},"popularity":{"monthly_downloads":183668,"position":10063,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.27.5"}