We present StreamVC, a streaming voice conversion solution that preserves the
content and prosody of any source speech while matching the voice timbre from
any target speech. Unlike previous approaches, StreamVC produces the resulting
waveform at low latency from the input signal even on a mobile platform, making
it applicable to real-time communication scenarios like calls and video
conferencing, and addressing use cases such as voice anonymization in these
scenarios. Our design leverages the architecture and training strategy of the
SoundStream neural audio codec for lightweight high-quality speech synthesis.
We demonstrate the feasibility of learning soft speech units causally, as well
as the effectiveness of supplying whitened fundamental frequency information to
improve pitch stability without leaking the source timbre information.

StreamVC 是一种流式语音转换解决方案，它能在保留源语音的内容和语调的同时，匹配任意目标语音的音色。与先前的方法不同，StreamVC 能在移动平台上以低延迟从输入信号生成结果波形，从而适用于实时通信场景，如电话和视频会议，并解决这些场景中的语音匿名化等问题。