#Text-To-Speech

Explore high-quality speech-to-text (STT) and text-to-speech (TTS) models designed for simplicity and performance. These models enable seamless, natural-sounding speech conversion across multiple languages, including Russian, English, German, and Spanish. Enhance text readability with automatic punctuation and capitalization, all with minimal setup using PyTorch, pip, or manual caching. Achieve efficient and reliable outcomes suited for diverse speech and text processing applications.

Discover the Pytorch implementation of the Tacotron model, a thorough end-to-end text-to-speech synthesis method. Utilizing the LJSpeech dataset, the project details steps from data preprocessing to audio synthesis. Aimed at researchers and developers in TTS technology, it allows hyperparameter adjustments to efficiently convert text to speech. Features include encoder, decoder, and post-processing networks essential for speech generation. The project is in early development stages, providing sample outputs and inviting community feedback for ongoing enhancement.

Explore a solution that automates Reddit TTS video creation through three integrated programs, balancing speed and quality. Manual review ensures content suitability and optimal thumbnails. Efficient YouTube API integration enhances engagement using familiar TTS voices and music. Ideal for leveraging the Reddit TTS trend.

This JavaScript adaptation of the 1982 Software Automatic Mouth (SAM) TTS software for the Commodore C64 includes a text-to-phoneme converter and phoneme-to-speech routine. Intended for low memory and file size, it allows users to implement it via 'yarn add sam-js' for functionalities like speech playback and wave file creation. While categorized as abandonware, it's notable for its efficient resource use, appealing to developers who need compact TTS solutions. Comprehensive insights and documents are accessible for more information.

The google-tts API for Node.js is a versatile tool for converting text to speech with options to generate audio URLs or Base64 encoded audio. It supports multiple languages and manages long texts through efficient segmentation. The adjustable speech speed and customizable host settings ensure adaptability for different regions. Easily integrated into JavaScript or TypeScript projects via npm, this solution offers reliable audio processing without complex setup.

Explore the TensorFlow implementation of Tacotron for end-to-end text-to-speech synthesis using publicly available datasets like LJ Speech. Gain insights into training processes, including hyperparameter adjustment, data downloading, and synthesis. Key features such as attention plot monitoring and gradient clipping offer valuable learning for TTS system advancements.