26 citations · 41 across the 9 of their papers we have counts for
9 papers
Video Forgery Detection with Optical Flow Residuals and Spatial-Temporal Consistency
Xi Xue, Kunio Suzuki, Nabarun Goswami +1
The rapid advancement of diffusion-based video generation models has led to increasingly realistic synthetic content, presenting new challenges for video forgery detection. Existin…
FUSE: Universal Speech Enhancement using Multi-Stage Fusion of Sparse Compression and Token Generation Models for the URGENT 2025 Challenge
Nabarun Goswami, Tatsuya Harada
We propose a multi-stage framework for universal speech enhancement, designed for the Interspeech 2025 URGENT Challenge. Our system first employs a Sparse Compression Network to ro…
ARTalk: Speech-Driven 3D Head Animation via Autoregressive Model
Xuangeng Chu, Nabarun Goswami, Ziteng Cui +2
Speech-driven 3D facial animation aims to generate realistic lip movements and facial expressions for 3D head models from arbitrary audio clips. Although existing diffusion-based m…
HyperVQ: MLR-based Vector Quantization in Hyperbolic Space
Nabarun Goswami, Yusuke Mukuta, Tatsuya Harada
The success of models operating on tokenized data has heightened the need for effective tokenization methods, particularly in vision and auditory tasks where inputs are naturally c…
Advancing Large Multi-modal Models with Explicit Chain-of-Reasoning and Visual Question Generation
Kohei Uehara, Nabarun Goswami, Hanqin Wang +10
The increasing demand for intelligent systems capable of interpreting and reasoning about visual content requires the development of large Vision-and-Language Models (VLMs) that ar…
The Sound Demixing Challenge 2023 $\unicode{x2013}$ Music Demixing Track
Giorgio Fabbro, Stefan Uhlich, Chieh-Hsin Lai +24
This paper summarizes the music demixing (MDX) track of the Sound Demixing Challenge (SDX'23). We provide a summary of the challenge setup and introduce the task of robust music so…
SATTS: Speaker Attractor Text to Speech, Learning to Speak by Learning to Separate
Nabarun Goswami, Tatsuya Harada
The mapping of text to speech (TTS) is non-deterministic, letters may be pronounced differently based on context, or phonemes can vary depending on various physiological and stylis…
Recursive speech separation for unknown number of speakers
Naoya Takahashi, Sudarsanam Parthasaarathy, Nabarun Goswami +1
In this paper we propose a method of single-channel speaker-independent multi-speaker speech separation for an unknown number of speakers. As opposed to previous works, in which th…
MMDenseLSTM: An efficient combination of convolutional and recurrent neural networks for audio source separation
Naoya Takahashi, Nabarun Goswami, Yuki Mitsufuji
Deep neural networks have become an indispensable technique for audio source separation (ASS). It was recently reported that a variant of CNN architecture called MMDenseNet was suc…