<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Zero-Shot on SoloSoft</title><link>https://www.solosoft.dev/tags/zero-shot/</link><description>Recent content in Zero-Shot on SoloSoft</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Fri, 01 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://www.solosoft.dev/tags/zero-shot/index.xml" rel="self" type="application/rss+xml"/><item><title>GPT-SoVITS: Few-Shot Voice Cloning with Just 1 Minute of Voice Data</title><link>https://www.solosoft.dev/post/gpt-sovits-voice-cloning-2026/</link><pubDate>Fri, 01 May 2026 00:00:00 +0000</pubDate><guid>https://www.solosoft.dev/post/gpt-sovits-voice-cloning-2026/</guid><description>&lt;p&gt;GPT-SoVITS is an open-source voice cloning and text-to-speech system developed by &lt;a href="https://github.com/RVC-Boss/GPT-SoVITS"&gt;RVC-Boss&lt;/a&gt; that has taken the AI audio community by storm. The project&amp;rsquo;s standout capability is few-shot voice cloning requiring just 1 minute of voice data to train a convincing voice model, with zero-shot capabilities using as little as 5-10 seconds of reference audio. Supporting Chinese, English, Japanese, and Korean, GPT-SoVITS combines the power of GPT-based autoregressive modeling with the spectral fidelity of SoVITS (Singing Voice Synthesis with Iterative refinement using a Transformer-based Sinkhorn).&lt;/p&gt;
&lt;p&gt;The project has amassed significant GitHub popularity by making professional-grade voice cloning accessible to anyone with a consumer GPU. Unlike commercial voice cloning services that charge per minute or require cloud uploads, GPT-SoVITS runs entirely locally, protecting user privacy and enabling unlimited usage. The quality has improved dramatically through iterative versions, with recent releases approaching studio-grade fidelity for trained voices.&lt;/p&gt;</description></item><item><title>IndexTTS-vLLM: Accelerated Open-Source Text-to-Speech with vLLM Inference</title><link>https://www.solosoft.dev/post/index-tts-vllm-2026/</link><pubDate>Fri, 01 May 2026 00:00:00 +0000</pubDate><guid>https://www.solosoft.dev/post/index-tts-vllm-2026/</guid><description>&lt;p&gt;Text-to-speech technology has advanced dramatically in the past three years. Zero-shot voice cloning, where a system can synthesize speech in a novel voice from just a few seconds of audio, went from research novelty to practical tool. Multi-speaker dialogue generation, where distinct voices can be mixed in a single output, moved from experimental to production-ready. The constraint holding these capabilities back from wider adoption has increasingly been inference speed — the gap between the quality of the output and the speed at which it can be generated.&lt;/p&gt;
&lt;p&gt;IndexTTS-vLLM addresses this gap directly. It is an accelerated version of the IndexTTS text-to-speech system that ports the model&amp;rsquo;s inference pipeline to run on vLLM, the high-performance inference engine originally developed for large language model serving. The result is a 2.5-3.5x speedup in TTS inference, enabling real-time speech synthesis with zero-shot voice cloning and multi-character audio mixing on consumer GPUs.&lt;/p&gt;</description></item></channel></rss>