{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/16"},{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/19"},{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/10"},{"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":"TTS is a deep learning library for text-to-speech synthesis that generates spoken audio from text using pretrained models across multiple languages, with support for model training and fine-tuning.","skillfed_tags":["speech-synthesis","deep-learning","voice-generation"],"use_cases":["Generate speech from text in applications requiring voice output, using pretrained models without training.","Train custom TTS models on proprietary voice datasets for domain-specific or branded voice synthesis.","Implement voice cloning by fine-tuning existing models with speaker-specific audio samples.","Build multilingual speech synthesis pipelines with language-specific models and tools.","Integrate TTS into web services or applications via the library's Flask-based server for synthesis."],"what_it_does":"TTS is a PyTorch-based library for neural text-to-speech synthesis that provides pretrained models and architectures including Tacotron2, Glow-TTS, VITS, XTTS, Bark, and Tortoise. It handles the full pipeline from text input to audio output, supporting both inference with released models and training custom models on new datasets.\n\nThe library depends on a substantial stack of 39 runtime packages: torch, torchaudio, scipy, librosa, scikit-learn, and language-specific tools including jieba, g2pkk, bangla, jamo, hangul-romanize, gruut, and pysbd. It includes vocoder models (MelGAN, HiFiGAN, ParallelWaveGAN) to convert spectrograms to waveforms, speaker encoders for multi-speaker synthesis, and utilities for dataset curation. Installation is straightforward via pip, though the dependency footprint and model downloads make it a medium-friction package.","worth_installing":"Yes, with conditions. Install if you need neural TTS synthesis and can accept the MPL-2.0 copyleft constraint and substantial dependency footprint. The library has recent commits and is in active use, but has not released since 2023-12-12. Avoid if you require active maintenance guarantees or proprietary licensing flexibility."},"id":"tts","links":{"html":"https://skillfed.io/packages/tts","md":"https://skillfed.io/packages/tts.md","pypi":"https://pypi.org/project/tts/"},"maintenance":{"status":"dormant"},"meta":{"latest_release":"2023-12-12","license_spdx":null,"license_treatment":"copyleft","name":"TTS","python_support":"capped_below_current","summary":"Deep learning for Text to Speech by Coqui."},"popularity":{"monthly_downloads":108143,"position":12574,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.22.0"}