VITS
An end-to-end text-to-speech synthesis model based on variational inference, capable of generating high-quality, natural-sounding speech. It supports multi-speaker synthesis and emotional control.
Timeline (last 90 days)
VITS is an end-to-end single-stage model that is typically 2–3 times faster than Tacotron2 on equivalent hardware and achieves higher quality.
End-to-end deep learning-based models such as WaveNet, VITS, and Voicebox have significantly improved audio quality and support speaking style transfer and zero-shot voice cloning.
Major players in the current voice synthesis market include Microsoft Azure TTS, Google Cloud TTS, OpenAI's TTS API, and open-source solutions such as Coqui TTS and VITS/VITS2.
End-to-end architectures such as Tacotron, FastSpeech, and VITS have compressed the overall text-to-audio latency from several seconds to hundreds of milliseconds.
VITS was proposed in 2021, unifying variational autoencoders, normalizing flows, and adversarial training into an end-to-end framework to achieve single-stage synthesis.
After 2020, end-to-end TTS models based on the Transformer architecture (such as FastSpeech 2 and VITS) integrated text analysis, prosody prediction, and waveform generation into a single model.
All Facts (9)
当前主流的神经网络TTS方案包括Tacotron系列、FastSpeech系列以及VITS、Bark等端到端模型
85%UnverifiedFish Speech底层采用了VITS架构的改进版本，将文本编码、韵律预测和声码器整合在一个端到端的框架中
70%UnverifiedModern neural network-based TTS models (such as Tacotron, VITS, GPT-SoVITS, etc.) can generate natural speech close to that of a real person, and support emotion control and voice timbre cloning.
60%UnverifiedVITS is an end-to-end single-stage model that is typically 2–3 times faster than Tacotron2 on equivalent hardware and achieves higher quality.
50%UnverifiedEnd-to-end deep learning-based models such as WaveNet, VITS, and Voicebox have significantly improved audio quality and support speaking style transfer and zero-shot voice cloning.
50%UnverifiedMajor players in the current voice synthesis market include Microsoft Azure TTS, Google Cloud TTS, OpenAI's TTS API, and open-source solutions such as Coqui TTS and VITS/VITS2.
50%UnverifiedEnd-to-end architectures such as Tacotron, FastSpeech, and VITS have compressed the overall text-to-audio latency from several seconds to hundreds of milliseconds.
50%UnverifiedVITS was proposed in 2021, unifying variational autoencoders, normalizing flows, and adversarial training into an end-to-end framework to achieve single-stage synthesis.
50%UnverifiedAfter 2020, end-to-end TTS models based on the Transformer architecture (such as FastSpeech 2 and VITS) integrated text analysis, prosody prediction, and waveform generation into a single model.
50%