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Found 7 papers, 0 papers with code
Linguistic Markers of Influence in Informal Interactions
There has been a long standing interest in understanding `Social Influence' both in Social Sciences and in Computational Linguistics.
Deep Neural Model Inspection and Comparison via Functional Neuron Pathways
We introduce a general method for the interpretation and comparison of neural models.
Semantic Complexity in End-to-End Spoken Language Understanding
We perform experiments where we vary the semantic complexity of a large, proprietary dataset and show that STI model performance correlates with our semantic complexity measures, such that performance increases as complexity values decrease.
Tie Your Embeddings Down: Cross-Modal Latent Spaces for End-to-end Spoken Language Understanding
In this paper, we treat an E2E system as a multi-modal model, with audio and text functioning as its two modalities, and use a cross-modal latent space (CMLS) architecture, where a shared latent space is learned between the `acoustic' and `text' embeddings.
Extreme Model Compression for On-device Natural Language Understanding
In this paper, we propose and experiment with techniques for extreme compression of neural natural language understanding (NLU) models, making them suitable for execution on resource-constrained devices.
End-to-End Spoken Language Understanding for Generalized Voice Assistants
End-to-end (E2E) spoken language understanding (SLU) systems predict utterance semantics directly from speech using a single model.
Ranked #10 on
Spoken Language Understanding
on Fluent Speech Commands
(using extra training data)
Quantization-Aware and Tensor-Compressed Training of Transformers for Natural Language Understanding
To improve the convergence, a layer-by-layer distillation is applied to distill a quantized and tensor-compressed student model from a pre-trained transformer.
