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🔍 daigo imamura 📂 Engineering
Showing 6 results for "daigo imamura" in Engineering
Engineering Preprint PDF DOI

MamTra: A Hybrid Mamba-Transformer Backbone for Speech Synthesis

Tan Dat Nguyen, Sangmin Bae, Joon Son Chung, Ji-Hoon Kim · 2026

Despite the remarkable quality of LLM-based text-to-speech systems, their reliance on autoregressive Transformers leads to quadratic computational complexity, which severely limits practical applicati…

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Engineering Preprint PDF DOI

On Ambisonic Source Separation with Spatially Informed Non-negative Tensor Factorization

Mateusz Guzik, Konrad Kowalczyk · 2025

This article presents a Non-negative Tensor Factorization based method for sound source separation from Ambisonic microphone signals. The proposed method enables the use of prior knowledge about the D…

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Engineering Preprint PDF DOI

A Spectral Estimation Framework for Phase Retrieval via Bregman Divergence Minimization

Bariscan Yonel, Birsen Yazici · 2020

In this paper, we develop a novel framework to optimally design spectral estimators for phase retrieval given measurements realized from an arbitrary model. We begin by deconstructing spectral methods…

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Engineering Preprint PDF DOI

Blind Audio Source Separation with Minimum-Volume Beta-Divergence NMF

Valentin Leplat, Nicolas Gillis, Man Shun Ang · 2019

Considering a mixed signal composed of various audio sources and recorded with a single microphone, we consider on this paper the blind audio source separation problem which consists in isolating and …

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Engineering Preprint PDF DOI

Sparse Gaussian Process Audio Source Separation Using Spectrum Priors in the Time-Domain

Pablo A. Alvarado, Mauricio A. Alvarez, Dan Stowell · 2018

Gaussian process (GP) audio source separation is a time-domain approach that circumvents the inherent phase approximation issue of spectrogram based methods. Furthermore, through its kernel, GPs elega…

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Engineering Preprint PDF DOI

PROSE: Perceptual Risk Optimization for Speech Enhancement

Jishnu Sadasivan, Chandra Sekhar Seelamantula, Nagarjuna Reddy Muraka · 2017

The goal in speech enhancement is to obtain an estimate of clean speech starting from the noisy signal by minimizing a chosen distortion measure, which results in an estimate that depends on the unkno…

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