2 citations · 4 across the 7 of their papers we have counts for
7 papers
Bagpiper-TTS: Natural Language Guided Universal Speech Synthesis
Jinchuan Tian, Haoran Wang, Siddhant Arora +6
Classical TTS systems typically rely on rigid input formats and predefined metadata slots, limiting their ability to fulfill flexible user requirements. This paper introduces Bagpi…
Online Predictive Coding for Dual-Mode Self-Supervised Speech Model
Keita Goto, Takashi Maekaku, Jin Sakuma +3
Dual-mode self-supervised speech models are pre-trained to handle streaming and non-streaming conditions simultaneously. However, their attention is computed over different context…
Online Register for Dual-Mode Self-Supervised Speech Models: Mitigating The Lack of Future Context
Keita Goto, Takashi Maekaku, Jin Sakuma +3
Dual-mode self-supervised speech models (S3Ms), which jointly pre-trained in the offline and online mode, suffer from attention mismatch in streaming scenarios due to missing futur…
Bagpiper: Solving Open-Ended Audio Tasks via Rich Captions
Jinchuan Tian, Haoran Wang, Bo-Hao Su +14
Current audio foundation models typically rely on rigid, task-specific supervision (e.g., speech recognition), addressing isolated factors of audio rather than the whole. In contra…
Conversation-oriented ASR with multi-look-ahead CBS architecture
Huaibo Zhao, Shinya Fujie, Tetsuji Ogawa +3
During conversations, humans are capable of inferring the intention of the speaker at any point of the speech to prepare the following action promptly. Such ability is also the key…
MLP-ASR: Sequence-length agnostic all-MLP architectures for speech recognition
Jin Sakuma, Tatsuya Komatsu, Robin Scheibler
We propose multi-layer perceptron (MLP)-based architectures suitable for variable length input. MLP-based architectures, recently proposed for image classification, can only be use…
Vocabulary Adaptation for Distant Domain Adaptation in Neural Machine Translation
Shoetsu Sato, Jin Sakuma, Naoki Yoshinaga +2
Neural network methods exhibit strong performance only in a few resource-rich domains. Practitioners, therefore, employ domain adaptation from resource-rich domains that are, in mo…