Papers with speech understanding tasks
SpeechLLMs for Large-scale Contextualized Zero-shot Slot Filling (2025.emnlp-industry)
Copied to clipboard
| Challenge: | Slot filling is a key subtask in spoken language understanding (SLU) . recent advent of speech-based large language models has opened new avenues for speech understanding . |
| Approach: | They propose to improve slot-filling task by creating an empirical upper bound for the task . they propose to use a speech-based large language model to integrate speech and text modalities . |
| Outcome: | The proposed model improves slot filling performance while reducing generalization gaps. |
SpikeVoice: High-Quality Text-to-Speech Via Efficient Spiking Neural Network (2024.acl-long)
Copied to clipboard
| Challenge: | SpikeVoice performs high-quality Text-To-Speech (TTS) via SNN . major obstacle to using SNN for such generative tasks lies in the demand for models to grasp long-term dependencies. |
| Approach: | They propose a brain-inspired Spiking Neural Network (SNN) which performs high-quality Text-To-Speech (TTS) via SNN and explores the potential of SNN to "speak". |
| Outcome: | The proposed model achieves comparable results to Artificial Neural Networks (ANN) with only 10.5% energy consumption of ANN. |
Unlocking Speech Instruction Data Potential with Query Rewriting (2025.findings-acl)
Copied to clipboard
| Challenge: | Existing LLMs lack datasets and biased training tasks to follow speech instructions. |
| Approach: | They propose a query rewriting framework that uses multiple agents to annotate and validate the synthesized speech. |
| Outcome: | The proposed framework can transform text instructions into distributions more suitable for TTS models for speech synthesis without human annotation. |