Natural Language Processing - IBM Research
Natural Language Processing Much of the information that can help transform enterprises is locked away in text, like documents, tables, and charts. We’re building advanced AI systems that can parse vast bodies of text to help unlock that data, but also ones flexible enough to be applied to any language problem.
IBM joins Stanford Human-Centered AI Institute’s partner program
Natural language processing (NLP) IBM is committed to exploring, creating and deploying technologies that make the world better, safer, and more prosperous for every single person. Unlocking the power of human language to connect, transform, inspire and organize holds the potential to deliver on that commitment.
自然语言处理中文期刊推荐? - 知乎
自然语言处理中文期刊推荐 自然语言处理 ( Natural Language Processing, NLP)是计算机科学领域与人工智能领域中的一个重要方向。它研究能实现人与计算机之间用自然语言进行有效通信的各种理论和方法。自然语言处理是一门融语言学、计算机科学、数学于一体的科学。因此,这一领域的研究将涉及自然 ...
语言学(linguistics)在人工智能(AI)的应用都有哪些? - 知乎
对语言有处理能力是人工智能的一种高级表现形式。人工智能领域的一个重要分支NLP(Natural Language Processing),就是根据传统语言学理论建立起来的。 这次 竹间智能 自然语言与深度学习小组 ,就从 NLP和NLU( Natural Language Understanding ) 角度来和大家分享一些语言学在AI中应用的经验。 传统的NLP包含 ...
A Tree-Based Statistical Language Model for Natural Language Speech ...
A Tree-Based Statistical Language Model for Natural Language Speech Recognition for IEEE Transactions on Acoustics, Speech, and Signal Processing by Lalit R. Bahl et al.
Sentiment analysis: Capturing favorability using natural language ...
Sentiment analysis: Capturing favorability using natural language processing for K-CAP 2003 by Tetsuya Nasukawa et al.
New Project Debater AI technologies available as cloud APIs
In February 2019 and after six years of work by natural language processing and machine learning researchers and engineers, an IBM AI dubbed Project Debater became the first AI system able to debate humans over complex topics.
Juan Bernabe Moreno - IBM Research
Work location IBM Research Europe - Ireland Dublin, Ireland Contact Topics Natural Language Processing Quantum Exploratory Science Data and AI Security Responsible Technology Fairness, Accountability, Transparency