Publications - Suresh Manandhar's Home Page

Designing an Interactive Open-domain Question Answering System

Silvia Quarteroni and Suresh Manandhar — 2007-08-27T11:12:29Z

To appear in the Journal of Natural Language Engineering (Special Issue on Interactive Question Answering) - Publications

Triphone Statistics for Polish Language

Bartosz Ziolko , Suresh Manandhar and Richard Wilson — 2007-10-30T14:15:55Z

The Polish text corpus was analysed to find information about phoneme statistics. We were especially interested in triphones as they are commonly used in many speech processing applications like HTK speech recogniser. An attempt to create the full list of triphones for Polish language is presented. A vast amount of phonetically transcribed text was analysed to obtain the frequency of triphone occurrences. A distibution of frequency of triphones occuring and other phenomena are presented. The standard phonetic alphabet for Polish and methods of providing phonetic transcriptions are described.

B. Ziolko, J. Galka, S. Manandhar, R. C. Wilson, M. Ziolko

Fuzzy Recall and Precision for Speech Segmentation Evaluation

Bartosz Ziolko , Suresh Manandhar and Richard Wilson — 2007-10-30T14:17:25Z

Proceedings of 3rd Language & Technology Conference, Poznan, Poland, 2007 Abstract: B. Ziolko, S. Manandhar, R. C. Wilson - Publications

User Modelling for Personalized Question Answering

Silvia Quarteroni and Suresh Manandhar — 2007-06-12T14:11:36Z

Proceedings of AI*IA 2007 - Publications

UOY: A Hypergraph Model for Word Sense Induction & Disambiguation

Ioannis P. Klapaftis and Suresh Manandhar — 2007-05-08T15:39:10Z

Proceedings of SensEval-4/SemEval-2007, Association for Computational Linguistics (ACL), Prague - Publications

Exploiting Syntactic and Shallow Semantic Kernels for Question/Answer Classification

2007-04-02T15:05:03Z

Proceedings of the 45th Conference of the Association for Computational Linguistics (ACL), Prague - Publications

A Chatbot-based Interactive Question Answering System

Suresh Manandhar and Silvia Quarteroni — 2007-09-04T14:39:24Z

In Proceedings of the 11th Workshop on the Semantics and Pragmatics of Dialogue (DECALOG), pages 83–90, Trento, Italy. - Publications

Advanced Structural Representations for Question Classification and Answer Re-ranking

2007-02-23T15:00:11Z

In this paper, we study novel structures to represent information in three vital tasks in question answering: question classification, answer classification and answer reranking.

We define a new tree structure called PAS to represent predicate-argument relations, as well as a new kernel function to exploit its representative power.

Our experiments with Support Vector Machines and several tree kernel functions suggest that syntactic information helps specific task as question classification, whereas, when data sparseness is higher as in answer classification, studying coarse semantic information like PAS is a promising research area.

Phoneme segmentation of speech

Bartosz Ziolko , Richard Wilson and Suresh Manandhar — 2007-02-27T17:57:20Z

In most approaches to speech recognition, the speech signals are segmented using constant-time segmentation, for example into 25 ms blocks. Constant segmentation risks losing information about the phonemes. Different sounds may be merged into single blocks and individual phonemes lost completely.

A more satisfactory approach is to attempt to segment the phoneme boundaries from the speech signals and use these boundaries to define blocks. The discrete wavelet transform (DWT) is interesting in the analysis of speech since it is easy to extract parameters which take into account the properties of the human hearing system. The analysis of the power in different frequency bands offers potential for distinguishing the start and end of phonemes. For many boundaries, there is no discernible drop in overall power, and at some frequencies, the power is broadly constant over the lifetime of the phoneme. However, many phonemes exhibit rapid changes in particular subbands which can be used to detect their start and endpoints.

In this paper we apply the DWT to speech signals and analyse the resulting power spectrum and its derivatives to locate candidates for the boundaries of phonemes in continuous speech. We compare the results with hand segmentation and constant segmentation over a number of words. The method proves effective for finding most phoneme boundaries.

Unsupervised Word Sense Disambiguation Using The WWW

Ioannis P. Klapaftis and Suresh Manandhar — 2006-06-05T12:05:17Z

Proceedings of STAIRS 2006, Italy - Publications