Real-Time Streaming Mel Vocoding with Generative Flow Matching

Simon Welker; Tal Peer; Timo Gerkmann

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arXiv · 2509.15085

Real-Time Streaming Mel Vocoding with Generative Flow Matching

Simon Welker·Tal Peer·Timo Gerkmann

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Abstract

The task of Mel vocoding, i.e., the inversion of a Mel magnitude spectrogram to an audio waveform, is still a key component in many text-to-speech (TTS) systems today. Based on generative flow matching, our prior work on generative STFT phase retrieval (DiffPhase), and the pseudoinverse operator of the Mel filterbank, we develop MelFlow, a streaming-capable generative Mel vocoder for speech sampled at 16 kHz with an algorithmic latency of only 32 ms and a total latency of 48 ms. We show real-time streaming capability at this latency not only in theory, but in practice on a consumer laptop GPU. Furthermore, we show that our model achieves substantially better PESQ and SI-SDR values compared to well-established not streaming-capable baselines for Mel vocoding including HiFi-GAN.

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BibTeX RIS

Simon Welker, Tal Peer, Timo Gerkmann. 2025-09-18. Real-Time Streaming Mel Vocoding with Generative Flow Matching. https://arxiv.org/abs/2509.15085

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