As the prevalence of social media on the Internet, opinion mining has become an essential
approach to analyzing so many data. Various applications appear in a wide range of …

KJS inside pages October 2016.indd Page 1 Kuwait J. Sci. 43 (4) pp. 95-113, 2016 A survey on
the state-of-the-art machine learning models in the context of NLP Wahab Khan1,*, Ali Daud2,1 …

Text to speech (TTS), or speech synthesis, which aims to synthesize intelligible and natural
speech given text, is a hot research topic in speech, language, and machine learning …

Deep learning methods employ multiple processing layers to learn hierarchical
representations of data, and have produced state-of-the-art results in many domains …

Twitter sentiment analysis technology provides the methods to survey public emotion about
the events or products related to them. Most of the current researches are focusing on …

Sentiment analysis of short texts such as single sentences and Twitter messages is
challenging because of the limited contextual information that they normally contain …

It is intuitive that NLP tasks for logographic languages like Chinese should benefit from the
use of the glyph information in those languages. However, due to the lack of rich …

Distributed word representations have recently been proven to be an invaluable resource for
NLP. These representations are normally learned using neural networks and capture …

It is desirable for dialog systems to have capability to express specific emotions during a
conversation, which has a direct, quantifiable impact on improvement of their usability and …

Currently most of state-of-the-art methods for Chinese word segmentation are based on
supervised learning, whose features are mostly extracted from a local context. These …