3 citations · 3 across the 6 of their papers we have counts for
5 papers · 1 filter
EZ-Ar-VC: Robust Arabic Voice Anonymization with Generalization across Dialects and Code-Switching
Injy Hamed, Adarsh Arigala, Rufael Marew +4
Voice conversion (VC) models can be used to anonymize speech data while preserving naturalness. Existing models, however, are mainly optimized for English and other high-resource l…
Cross-Lingual TTS for Indian Languages: A Benchmark and Inference-Time Duration Estimation Strategies
Adarsh Arigala, Arjun Gangwar, Srinivasan Umesh
Recent alignment-free Text-to-Speech (TTS) models achieve high synthesis quality by removing explicit alignment modules and simplifying training. However, they often struggle in cr…
HybridCodec: Fast Dual-Stream, Semantically Enhanced Neural Audio Codec
Arjun Gangwar, S Umesh
The popularity of neural audio codecs as speech tokenizers has surged with the advent of Multimodal Large Language Models. New codec architectures with semantic and acoustic disent…
Multilingual Multi-Speaker Unit Vocoders: A Systematic Analysis of Discrete Speech Representations
Naman Kothari, Arjun Gangwar, Adarsh Arigala +1
Discrete speech units obtained via k-means clustering of self supervised embeddings entangle phonetic, speaker, and language information, causing speaker mixing and cross-lingual i…
Pixel-TTS: Image based Text Rendering for Robust Text-to-Speech
Adarsh Arigala, Arjun Gangwar, S Umesh +1
Recent advances in pixel-based text modeling show that representing text as images enables models to exploit visual cues for language understanding. Grounding text in its visual fo…