Work

Offline Urdu Text to Speech for iOS with Distilled Matcha

Year: 2026

Type: preprint

Abstract: QnVoice distills a pinned Urdu Matcha acoustic model to three flow steps with a learned mel correction and runs HiFi-GAN offline. On an iPhone 15 Pro, median warm synthesis time fell from 1.50 s to 1.30 s across 72 runs per model. The companion project contains the ONNX files, benchmark records, and paired samples. Native-speaker listening tests and commercial release review remain pending.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.24029948

Author: QnVoice

Language: English

Topic: Speech Recognition and Synthesis

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7225459497

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