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Found 5 papers, 1 papers with code
基于改进Conformer的新闻领域端到端语音识别(End-to-End Speech Recognition in News Field based on Conformer)
“目前, 开源的中文语音识别数据集多为面向通用领域, 缺少面向新闻领域的开源语音识别语料库, 因此本文构建了面向新闻领域的中文语音识别数据集CHNEWSASR并使用ESPNET-0. 9. 6框架的RNN、Transformer和Conformer等模型对数据集的有效性进行了验证, 实验表明本文所构建的语料在最好的模型上CER为4. 8%, SER为39. 4%。由于新闻联播主持人说话语速相对较快, 本文构建的数据集文本平均长度为28个字符是Aishell1数据集文本平均长度的2倍, 且以往的研究中训练目标函数通常为基于字或词水平, 缺乏明确的句子水平关系, 因此本文提出了一个句子层级的一致性模块与Conformer模型结合直接减少源语音和目标文本的表示差异, 在开源的Aishell1数据集上其CER降低0. 4%, SER降低2%;在CHNEWSASR数据集上其CER降低0. 9%, SER降低3%, 实验结果表明该方法不提升模型参数量的前提下能有效提升语音识别的质量。”
MFHCA: Enhancing Speech Emotion Recognition Via Multi-Spatial Fusion and Hierarchical Cooperative Attention
This paper introduces MFHCA, a novel method for Speech Emotion Recognition using Multi-Spatial Fusion and Hierarchical Cooperative Attention on spectrograms and raw audio.
The Ninth NTIRE 2024 Efficient Super-Resolution Challenge Report
In sub-track 1, the practical runtime performance of the submissions was evaluated, and the corresponding score was used to determine the ranking.
Pay Self-Attention to Audio-Visual Navigation
Audio-visual embodied navigation, as a hot research topic, aims training a robot to reach an audio target using egocentric visual (from the sensors mounted on the robot) and audio (emitted from the target) input.
Revenue and Energy Efficiency-Driven Delay Constrained Computing Task Offloading and Resource Allocation in a Vehicular Edge Computing Network: A Deep Reinforcement Learning Approach
In this paper, we propose a joint task type and vehicle speed-aware task offloading and resource allocation strategy to decrease the vehicl's energy cost for executing tasks and increase the revenue of the vehicle for processing tasks within the delay constraint.
