Ridong Jiang

Evaluating and Combining Name Entity Recognition Systems.

Name entity recognition (NER) is an important subtask in natural language processing. Various NER systems have been developed in the last decade. They may target for different domains, employ different methodologies, work on different languages, detect different types of entities, and support different inputs and output formats. These conditions make it difficult for a user to select the right NER tools for a specific task. Motivated by the need of NER tools in our research work, we select several publicly available and well-established NER tools to validate their outputs against both Wikipedia gold standard corpus and a small set of manually annotated documents. All the evaluations show consistent results on the selected tools. Finally, we constructed a hybrid NER tool by combining the best performing tools for the domains of our interest.

Component Pluggable Dialogue Framework and Its Application to Social Robots

This paper is concerned with the design and development of a component pluggable event-driven dialogue framework for service robots. We abstract standard dialogue functions and encapsulate them into different types of components or plug-ins. A component can be a hardware device, a software module, an algorithm or a database connection. The framework is empowered by a multipurpose XML-based dialogue engine, which is capable for pipeline information flow construction, event mediation, multi-topic dialogue modeling and different types of knowledge representation. The framework is domain-independent, cross-platform, and multilingual. Experiments on various service robots in our social robotics laboratory showed that the same framework works for all the robots that need speech interface. The development cycle for new dialogue system is greatly shortened while the system robustness, reliability, and maintainability are significantly improved.

SARA: Singapore’s Automated Responsive Assistant, A Multimodal Dialogue System for Touristic Information

In this paper we describe SARA, a multimodal dialogue system offering touristic assistance for visitors coming to Singapore. The system is implemented as an Android mobile phone application and provides information about local attractions, restaurants, sightseeing, direction and transportation services. SARA is able to detect the user’s location on a map by using a GPS integrated module and accordingly can provide real-time orientation and direction help. To communicate with SARA users can use speech, text or scanned QR code. Input/output modalities for SARA include natural language in form of speech or text. A short video about the main features of our Android application can be seen at: http://vimeo.com/91620644. Currently, the system supports only English, but we are working towards a multi-lingual input/output support. For test purposes we also created a web version of SARA that can be tested for Chinese and English text input/output at: http://iris.i2r.a-star.edu.sg/StatTour/.

Experiences with a Barista Robot, FusionBot

In this paper, we describe the implemented service robot, called FusionBot. The goal of this research is to explore and demonstrate the utility of an interactive service robot in a smart home environment, thereby improving the quality of human life. The robot has four main features: 1) speech recognition, 2) object recognition, 3) object grabbing and fetching and 4) communication with a smart coffee machine. Its software architecture employs a multimodal dialogue system that integrates different components, including spoken dialog system, vision understanding, navigation and smart device gateway. In the experiments conducted during the TechFest 2008 event, the FusionBot successfully demonstrated that it could autonomously serve coffee to visitors on their request. Preliminary survey results indicate that the robot has potential to not only aid in the general robotics but also contribute towards the long term goal of intelligent service robotics in smart home environment.

CLARA: A Multifunctional Virtual Agent for Conference Support and Touristic Information

In this paper we present a multifunctional conversational agent which combines natural language search capabilities for two different domain applications: a conference information system and local tourist guide. The paper describes the corpora, architecture, algorithm, and the mobile application created to interact with the users. Finally, some results obtained when using the proposed system in the context of an international scientific conference held in Singapore in September 2014 with more than 1200 assistants are provided.

Design and evaluation of a conversational agent for the touristic domain

This paper focuses on the design and evaluation of SARA, a conversational agent for the touristic domain featuring a high number of different, unique characteristics: spoken dialogue interaction, dialogue orchestration, context dependent information, an animated avatar and support for different kind of dialogue types, i.e. chat, specific and general question-answering, task oriented dialogues. The agent has currently two implementations: as web client and as mobile phone application. The paper describes the modules and resources required for running the agent on both interfaces, as well as the evaluation results obtained from two assessment studies concerning the interaction design of these two agent interfaces. The feedback gathered from the studies will enable us to improve the applications in terms of service, performance and usability.

An Interactive Robot Butler

This paper describes a novel robotic butler, developed by a multi-disciplinary team of researchers. The robotic butler is capable of detecting and tracking human, recognize hand gestures, serving beverages and performs dialog conversation with guest about their interests and their preferences; and providing specific information on the facilities at Fusionopolis building and various technologies used by the robot. The robot employs an event driven dialogue management system (DMS) architecture, speech recognition, ultra wideband, vision understanding and radio frequency identification. All these components and agents that are integrated in the DMS architecture are modular and can be re-used by other applications. In this paper, we will first describe the design concept and the architecture of the robotic butler. Secondly, we will describe in detail the workings of the speech and vision technology as this paper mainly focuses on human-robot interaction aspects of the social robot. Lastly, this paper will highlight some key challenges that were faced during the implementation of speech and vision technology into the robot.

Towards improving the performance of Vector Space Model for Chinese Frequently Asked Question Answering

This paper presents a method which improves the performance of Vector Space Model (VSM) when applying it to Chinese Frequently Asked Questions (FAQ). This method combines unigram and bigram models in determining the similarity of document vectors. The performance is further improved by applying shallow lexical semantics and the document length information. Experiments showed that the proposed methods outperform baselines (segmentation and bigram) across different datasets which include FAQs from restricted domains and open domains.

Configuration of dialogue agent with multiple knowledge sources

Knowledge base is a key component of a dialogue agent which determines its usability, performance as well as intelligence. Usually one type of knowledge source is tailored towards specific application or task. One challenge for developing multiple-domain dialogue agents is how to represent the domain knowledge in their respective ways for the best efficiency and easy construction of queries from natural language. There are a variety of knowledge sources available for building up dialogue agents such as relational database, ontology, knowledge base (KB), search index, artificial intelligence markup language (AIML) and the World Wide Web, etc. In this paper, we present a systematic way of configuring dialogue agents supported by multiple knowledge sources. With the proposed dialogue framework, we provide a complete solution for the development of various dialogue systems with the support of different dialogue management techniques, multiple protocols for cloud-enabled dialogue services, pluggable infrastructure for component reuse and service enhancement, strong scripting functions in both XML and Python. We have constructed various dialogue agents with this framework. Results show that these agents are robust and the development cycle can be considerably reduced.