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Found 4 papers, 0 papers with code
Mapping Local News Coverage: Precise location extraction in textual news content using fine-tuned BERT based language model
Mapping local news coverage from textual content is a challenging problem that requires extracting precise location mentions from news articles.
Improving vision-inspired keyword spotting using dynamic module skipping in streaming conformer encoder
Using a vision-inspired keyword spotting framework, we propose an architecture with input-dependent dynamic depth capable of processing streaming audio.
Flexible Keyword Spotting based on Homogeneous Audio-Text Embedding
Spotting user-defined/flexible keywords represented in text frequently uses an expensive text encoder for joint analysis with an audio encoder in an embedding space, which can suffer from heterogeneous modality representation (i. e., large mismatch) and increased complexity.
Matching Latent Encoding for Audio-Text based Keyword Spotting
Using audio and text embeddings jointly for Keyword Spotting (KWS) has shown high-quality results, but the key challenge of how to semantically align two embeddings for multi-word keywords of different sequence lengths remains largely unsolved.
