mlsanityData to 7 Oct 2026

VANI: Very-lightweight Accent-controllable TTS for Native and Non-native speakers with Identity Preservation

arXiv 2303.07578 ↗First posted 14 Mar 2023cs.SD cs.LG eess.AScited by 2

Not on the map. Why?

Abstract (arXiv)

We introduce VANI, a very lightweight multi-lingual accent controllable speech synthesis system. Our model builds upon disentanglement strategies proposed in RADMMM and supports explicit control of accent, language, speaker and fine-grained F0 and energy features for speech synthesis. We utilize the Indic languages dataset, released for LIMMITS 2023 as part of ICASSP Signal Processing Grand Challenge, to synthesize speech in 3 different languages. Our model supports transferring the language of a speaker while retaining their voice and the native accent of the target language. We utilize the large-parameter RADMMM model for Track 1 and lightweight VANI model for Track 2 and 3 of the competition.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 2 of its 3 references that are in the map. First posted on arXiv 14 Mar 2023.

Builds on

2 of 3 references.

References · 2

  1. 2021TitaNet: Neural Model for speaker representation with 1D Depth-wise separable convolutions and global contextcited by 61
  2. 2020Flowtron: an Autoregressive Flow-based Generative Network for Text-to-Speech Synthesiscited by 54

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 0; 2026: 1.

2 papers.