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Found 5 papers, 1 papers with code
Text-to-Edit: Controllable End-to-End Video Ad Creation via Multimodal LLMs
The exponential growth of short-video content has ignited a surge in the necessity for efficient, automated solutions to video editing, with challenges arising from the need to understand videos and tailor the editing according to user requirements.
LatentSync: Audio Conditioned Latent Diffusion Models for Lip Sync
Since we did not change the overall training framework of SyncNet, our experience can also be applied to other lip sync and audio-driven portrait animation methods that utilize SyncNet.
Speech2Slot: An End-to-End Knowledge-based Slot Filling from Speech
In contrast to conventional pipeline Spoken Language Understanding (SLU) which consists of automatic speech recognition (ASR) and natural language understanding (NLU), end-to-end SLU infers the semantic meaning directly from speech and overcomes the error propagation caused by ASR.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+8
Understanding Semantics from Speech Through Pre-training
End-to-end Spoken Language Understanding (SLU) is proposed to infer the semantic meaning directly from audio features without intermediate text representation.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
Quantifying Context Overlap for Training Word Embeddings
Most models for learning word embeddings are trained based on the context information of words, more precisely first order co-occurrence relations.
