Search Results for "extract-xiso"

Voice-Pro is the best gradio WebUI for transcription, translation and text-to-speech. It can be easily installed with one click. Create a virtual environment using Miniconda, running completely separate from the Windows system (fully portable). Supports real-time transcription and translation, as well as batch mode.

...From version 0.96 onward, ffmpeg installation is required for deployment, and previous CSV/PT voice tables are no longer valid, so users instead work with updated “voice value” parameters. For convenience, there is a prepackaged Windows build: you download a release archive, extract it, and double-click app.exe to start the web UI, which opens on localhost:9966.

...Powered by the state-of-the-art Kokoro-82M neural engine, AudioBC produces natural, human-like speech that rivals premium cloud services. It is built with a focus on privacy and simplicity, offering a streamlined three-step workflow: Extract, Edit, and Convert. Key Features: Neural Quality TTS: Uses the compact yet powerful Kokoro-82M model for high-fidelity, expressive voice synthesis. Privacy-First & Offline: After a one-time initial model download, all processing happens on your CPU. Your books never leave your computer. Multi-Language Support: Curated voices for English (US & UK), Italian, French, Spanish, and Portuguese (BR). ...

VoiceFixer is a machine-learning framework for “speech restoration”: given a degraded or distorted audio recording — with noise, clipping, low sampling rate, reverberation, or other artifacts — it attempts to recover high-fidelity, clean speech. The architecture works in two stages: first an analysis stage that tries to extract “clean” intermediate features from the noisy audio (e.g. removing noise, denoising, dereverberation, upsampling), and then a neural vocoder-based synthesis stage that reconstructs a high-quality waveform from those features. Unlike many single-purpose noise reduction tools, VoiceFixer targets a “general speech restoration” problem (GSR), capable of handling multiple types of distortions at once, which makes it suitable for old recordings, phone-call audio, amateur voice recordings, or archival media. ...

...It takes inspiration from architectures like FastSpeech, FastSpeech 2, FastPitch, and Transformer TTS, and extends them with its own aligner and forward models. The system separates alignment learning and acoustic modeling: an autoregressive Transformer is used as an aligner to extract phoneme-to-frame durations, while a non-autoregressive “ForwardTransformer” generates mel-spectrograms conditioned on text and durations. This design addresses common autoregressive issues such as repetition, skipped words, and unstable attention, and results in robust, fast synthesis where all frames are predicted in parallel. ...