Prediction of Depression Severity Based on the Prosodic and Semantic Features with Bidirectional LSTM and Time Distributed CNN

no code implementations • 25 Feb 2022 • Kaining Mao, Wei zhang, Deborah Baofeng Wang, Ang Li, Rongqi Jiao, Yanhui Zhu, Bin Wu, Tiansheng Zheng, Lei Qian, Wei Lyu, Minjie Ye, Jie Chen

For the text modality, we use global vectors for word representation (GloVe) to perform word embeddings and the embeddings are fed into the Bi-LSTM network.

Depression Detection Word Embeddings

Performance Evaluation of Channel Decoding With Deep Neural Networks

1 code implementation • 1 Nov 2017 • Wei Lyu, Zhaoyang Zhang, Chunxu Jiao, Kangjian Qin, Huazi Zhang

With the demand of high data rate and low latency in fifth generation (5G), deep neural network decoder (NND) has become a promising candidate due to its capability of one-shot decoding and parallel computing.