1 citations · 1 across the 9 of their papers we have counts for
9 papers
Grounded Decoding for Autoregressive Speech Enhancement via Adaptive Code-Space Grounding and Local LLM Refinement
Hao Shi, Yuan Gao, Zhaoheng Ni +4
Large language model (LLM)-based autoregressive speech enhancement (SE) produces natural speech using learned clean-speech priors, but may hallucinate content unsupported by the in…
Optimal Transport-based Semantic Alignment for LLM-based Audio-Visual Speech Recognition
Xugang Lu, Peng Shen, Yu Tsao +1
Large language model (LLM)-based audio-visual speech recognition (LLM-AVSR) has recently demonstrated strong robustness in adverse acoustic environments by leveraging complementary…
Beyond Acoustic Prefixes: Persistent Access to Serialized Acoustic Memory for LLM-Based Multi-Talker Speech Recognition
Hao Shi, Yuan Gao, Xugang Lu +1
Large language models (LLMs) provide strong linguistic priors for serialized output training (SOT), yet LLM-based multi-talker ASR degrades substantially as the number of overlappi…
New Insights into Optimal Alignment of Acoustic and Linguistic Representations for Knowledge Transfer in ASR
Xugang Lu, Peng Shen, Hisashi Kawai
Aligning acoustic and linguistic representations is a central challenge to bridge the pre-trained models in knowledge transfer for automatic speech recognition (ASR). This alignmen…
Cross-modal Knowledge Transfer Learning as Graph Matching Based on Optimal Transport for ASR
Xugang Lu, Peng Shen, Yu Tsao +1
Transferring linguistic knowledge from a pretrained language model (PLM) to acoustic feature learning has proven effective in enhancing end-to-end automatic speech recognition (E2E…
Retrieval-Augmented Speech Recognition Approach for Domain Challenges
Peng Shen, Xugang Lu, Hisashi Kawai
Speech recognition systems often face challenges due to domain mismatch, particularly in real-world applications where domain-specific data is unavailable because of data accessibi…
Temporal Order Preserved Optimal Transport-based Cross-modal Knowledge Transfer Learning for ASR
Xugang Lu, Peng Shen, Yu Tsao +1
Transferring linguistic knowledge from a pretrained language model (PLM) to an acoustic model has been shown to greatly improve the performance of automatic speech recognition (ASR…
Generative linguistic representation for spoken language identification
Peng Shen, Xuguang Lu, Hisashi Kawai
Effective extraction and application of linguistic features are central to the enhancement of spoken Language IDentification (LID) performance. With the success of recent large mod…
Speaker Mask Transformer for Multi-talker Overlapped Speech Recognition
Peng Shen, Xugang Lu, Hisashi Kawai
Multi-talker overlapped speech recognition remains a significant challenge, requiring not only speech recognition but also speaker diarization tasks to be addressed. In this paper,…