activity
20232026
most citedEFFUSE: Efficient Self-Supervised Feature Fusion for E2E ASR in Low Resource and Multilingual Scenarios

2 citations · 3 across the 14 of their papers we have counts for

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12 papers · 1 filter

cs.SD2025

SingingSDS: A Singing-Capable Spoken Dialogue System for Conversational Roleplay Applications

Jionghao Han, Jiatong Shi, Masao Someki +5

With recent advances in automatic speech recognition (ASR), large language models (LLMs), and text-to-speech (TTS) technologies, spoken dialogue systems (SDS) have become widely ac…

cs.SD2025

Adapting Speech Language Model to Singing Voice Synthesis

Yiwen Zhao, Jiatong Shi, Jinchuan Tian +4

Speech Language Models (SLMs) have recently emerged as a unified paradigm for addressing a wide range of speech-related tasks, including text-to-speech (TTS), speech enhancement (S…

cs.SD2025

Robust Training of Singing Voice Synthesis Using Prior and Posterior Uncertainty

Yiwen Zhao, Jiatong Shi, Yuxun Tang +2

Singing voice synthesis (SVS) has seen remarkable advancements in recent years. However, compared to speech and general audio data, publicly available singing datasets remain limit…

cs.SD2025

CartoonSing: Unifying Human and Nonhuman Timbres in Singing Generation

Jionghao Han, Jiatong Shi, Zhuoyan Tao +4

Singing voice synthesis (SVS) and singing voice conversion (SVC) have achieved remarkable progress in generating natural-sounding human singing. However, existing systems are restr…

cs.SD2024

Muskits-ESPnet: A Comprehensive Toolkit for Singing Voice Synthesis in New Paradigm

Yuning Wu, Jiatong Shi, Yifeng Yu +7

This research presents Muskits-ESPnet, a versatile toolkit that introduces new paradigms to Singing Voice Synthesis (SVS) through the application of pretrained audio models in both…

cs.SD2024

MMM: Multi-Layer Multi-Residual Multi-Stream Discrete Speech Representation from Self-supervised Learning Model

Jiatong Shi, Xutai Ma, Hirofumi Inaguma +2

Speech discrete representation has proven effective in various downstream applications due to its superior compression rate of the waveform, fast convergence during training, and c…