6 papers
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…
ESPnet3: Infrastructure for Scalable Speech and Audio Research in the Foundation Model Era
Masao Someki, Alexander Polok, Carlos Carvalho +14
Recent speech research involves increasingly large datasets, complex models, and diverse experimental workflows. However, existing frameworks require substantial engineering effort…
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…
Towards Inclusive ASR: Investigating Voice Conversion for Dysarthric Speech Recognition in Low-Resource Languages
Chin-Jou Li, Eunjung Yeo, Kwanghee Choi +7
Automatic speech recognition (ASR) for dysarthric speech remains challenging due to data scarcity, particularly in non-English languages. To address this, we fine-tune a voice conv…
On-device Streaming Discrete Speech Units
Kwanghee Choi, Masao Someki, Emma Strubell +1
Discrete speech units (DSUs) are derived from clustering the features of self-supervised speech models (S3Ms). DSUs offer significant advantages for on-device streaming speech appl…
Context-Driven Dynamic Pruning for Large Speech Foundation Models
Masao Someki, Shikhar Bharadwaj, Atharva Anand Joshi +7
Speech foundation models achieve strong generalization across languages and acoustic conditions, but require significant computational resources for inference. In the context of sp…