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EmoReg: Directional Latent Vector Modeling for Emotional Intensity Regularization in Diffusion-based Voice Conversion
Ashishkumar Gudmalwar, Ishan D. Biyani, Nirmesh Shah +2
The Emotional Voice Conversion (EVC) aims to convert the discrete emotional state from the source emotion to the target for a given speech utterance while preserving linguistic con…
DubWise: Video-Guided Speech Duration Control in Multimodal LLM-based Text-to-Speech for Dubbing
Neha Sahipjohn, Ashishkumar Gudmalwar, Nirmesh Shah +2
Audio-visual alignment after dubbing is a challenging research problem. To this end, we propose a novel method, DubWise Multi-modal Large Language Model (LLM)-based Text-to-Speech…
VECL-TTS: Voice identity and Emotional style controllable Cross-Lingual Text-to-Speech
Ashishkumar Gudmalwar, Nirmesh Shah, Sai Akarsh +2
Despite the significant advancements in Text-to-Speech (TTS) systems, their full utilization in automatic dubbing remains limited. This task necessitates the extraction of voice id…
Isometric Neural Machine Translation using Phoneme Count Ratio Reward-based Reinforcement Learning
Shivam Ratnakant Mhaskar, Nirmesh J. Shah, Mohammadi Zaki +3
Traditional Automatic Video Dubbing (AVD) pipeline consists of three key modules, namely, Automatic Speech Recognition (ASR), Neural Machine Translation (NMT), and Text-to-Speech (…