no code implementations • LREC 2020 • Eric Chen, Zhiyun Lu, Hao Xu, Liangliang Cao, Yu Zhang, James Fan
We present a multimodal corpus for sentiment analysis based on the existing Switchboard-1 Telephone Speech Corpus released by the Linguistic Data Consortium.
no code implementations • 21 Nov 2019 • Zhiyun Lu, Liangliang Cao, Yu Zhang, Chung-Cheng Chiu, James Fan
In this paper, we propose to use pre-trained features from end-to-end ASR models to solve speech sentiment analysis as a down-stream task.
no code implementations • 22 Sep 2015 • Nikolai Yakovenko, Liangliang Cao, Colin Raffel, James Fan
The contributions of this paper include: (1) a novel representation for poker games, extendable to different poker variations, (2) a CNN based learning model that can effectively learn the patterns in three different games, and (3) a self-trained system that significantly beats the heuristic-based program on which it is trained, and our system is competitive against human expert players.
no code implementations • 4 Feb 2014 • Gerald Tesauro, David C. Gondek, Jonathan Lenchner, James Fan, John M. Prager
After giving a detailed description of each of our game-strategy algorithms, we then focus in particular on validating the accuracy of the simulators predictions, and documenting performance improvements using our methods.