With the continuous development of information technology and the rapid increase in new
users of social networking sites, recommendation technology is becoming more and more …

Recently, speech-text pre-training methods have shown remarkable success in many
speech and natural language processing tasks. However, most previous pre-trained models …

We introduce EM-Network, a novel self-distillation approach that effectively leverages target
information for supervised sequence-to-sequence (seq2seq) learning. In contrast to …

Recently, speech-text pre-training methods have shown remarkable success in many
speech and natural language processing tasks. However, most previous pre-trained models …

Speech data has rich acoustic and paralinguistic information with important cues for
understanding a speaker's tone, emotion, and intent, yet traditional large language models …

Recent advancements in joint speech-text pre-training have significantly advanced the
processing of natural language. However, a key limitation is their reliance on parallel …

Traditional large language models (LLMs) leverage extensive text corpora but lack access to
acoustic and para-linguistic cues present in speech. There is a growing interest in …

The review delves into creating an understandable framework for machine learning in
robotics. It stresses the significance of machine learning in materials science and robotics …

Recently, sequence-to-sequence learning has shown remarkable performance in speech
and natural language processing. However, high-performing sequence models commonly …