2 citations · 2 across the 14 of their papers we have counts for
14 papers
AURA: Uncertainty-Routed Activation Editing for Acoustic Grounding in Speech Foundation Models
Natarajan Balaji Shankar, Zilai Wang, Zihan Wang +3
Attention encoder-decoder (AED) Speech Foundation Models achieve strong ASR performance but can generate acoustically unsupported text when inputs contain no speech, weak acoustic…
Gumbel-BEARD: Automatic Layer Selection for Self-Supervised Adaptation of Whisper in Low-Resource Domains
Zilai Wang, Natarajan Balaji Shankar, Mohan Shi +2
Speech foundation models often struggle in low-resource domains due to domain mismatch and data scarcity. We propose Gumbel-BEARD, a domain adaptation framework that automates Whis…
GC-LoRA: Gated Convolutional LoRA for Parameter-Efficient Acoustic Adaptation
Natarajan Balaji Shankar, Zilai Wang, Kaiyuan Zhang +2
Transformer-based Speech Foundation Models excel in most Automatic Speech Recognition tasks but often suffer performance degradation when applied to domains with mismatched acousti…
Entropy-Aware Domain-Routed Mixture-of-Experts Speech-LLM Framework: A Case Study of Multi-Domain Child-Adult ASR
Mohan Shi, Kaiyuan Zhang, Zilai Wang +3
While Speech Large Language Models (Speech-LLMs) have achieved strong performance on adult Automatic Speech Recognition (ASR), their effectiveness on child speech remains under-exp…
STACodec: Semantic Token Assignment for Balancing Acoustic Fidelity and Semantic Information in Audio Codecs
Kaiyuan Zhang, Mohan Shi, Eray Eren +3
Neural audio codecs are widely used for audio compression and can be integrated into token-based language models. Traditional codecs preserve acoustic details well but lack semanti…
Mind the Shift: Using Delta SSL Embeddings to Enhance Child ASR
Zilai Wang, Natarajan Balaji Shankar, Kaiyuan Zhang +2
Self-supervised learning (SSL) models have achieved impressive results across many speech tasks, yet child automatic speech recognition (ASR) remains challenging due to limited dat…