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Speech Discrete Tokens or Continuous Features? A Comparative Analysis for Spoken Language Understanding in SpeechLLMs
Dingdong Wang, Junan Li, Mingyu Cui +3
With the rise of Speech Large Language Models (SpeechLLMs), two dominant approaches have emerged for speech processing: discrete tokens and continuous features. Each approach has d…
MMSU: A Massive Multi-task Spoken Language Understanding and Reasoning Benchmark
Dingdong Wang, Junan Li, Jincenzi Wu +4
Speech inherently contains rich acoustic information that extends far beyond the textual language. In real-world spoken language understanding, effective interpretation often requi…
DiffDSR: Dysarthric Speech Reconstruction Using Latent Diffusion Model
Xueyuan Chen, Dongchao Yang, Wenxuan Wu +5
Dysarthric speech reconstruction (DSR) aims to convert dysarthric speech into comprehensible speech while maintaining the speaker's identity. Despite significant advancements, exis…
ALMTokenizer: A Low-bitrate and Semantic-rich Audio Codec Tokenizer for Audio Language Modeling
Dongchao Yang, Songxiang Liu, Haohan Guo +9
Recent advancements in audio language models have underscored the pivotal role of audio tokenization, which converts audio signals into discrete tokens, thereby facilitating the ap…
AV-TSE: Context and Confidence-aware Audio Visual Target Speaker Extraction
Wenxuan Wu, Xueyuan Chen, Shuai Wang +5
Audio-Visual Target Speaker Extraction (AV-TSE) aims to mimic the human ability to enhance auditory perception using visual cues. Although numerous models have been proposed recent…