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Intelligibility of modifications to dysarthric speech

Intelligibility of modifications to dysarthric speech

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international conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： J.-P. Hosom A.B. Kain T. Mishra J.P.H. van Santen M. Fried-Oken J. Staehely Center for Spoken Language Understanding OGI School of Science and Engineering USA Assistive Technology Program Child Development and Rehabilitation Center Oregon Health and Sciences University Portland OR USA

Dysarthria is a motor speech impairment affecting millions of people. Dysarthric speech can be far less intelligible than that of non-dysarthric speakers, causing significant communication difficulties. The goal of our work is to understand the effect that certain modifications have on the intelligibility of dysarthric speech. These modifications are designed to identify aspects of the speech signal or signal processing that may be especially relevant to the effectiveness of a system that transforms dysarthric speech to improve its intelligibility. A result of this study is that dysarthric speech can, in the best case, be modified only at the short-term spectral level to improve intelligibility from 68% to 87%. A baseline transformation system using standard technology, however, does not show improvement in intelligibility. Prosody also has a significant (p<0.05) effect on intelligibility.

关键词： Signal processing Speech processing Speech synthesis Signal design Speech recognition natural languages Pediatrics Multiple sclerosis Muscles Filters

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Triphone model reconstruction for Mandarin pronunciation variations

Triphone model reconstruction for Mandarin pronunciation var...

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international conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： P. Fung Liu Yi Human Language Technology Center Department of Electrical and Electronic Engineering University of Science and Technology (HKUST) Hong Kong China

The high error rate of recognition accuracy in spontaneous speech is due in part to the poor modeling of pronunciations. In this paper, we propose modeling pronunciation variations through triphone model reconstruction. We first generate a partial change phone model (PCPM) to differentiate pronunciation variations. In order to improve the resolution of triphone models, PCPM is used as a hidden model and merged into the pre-trained acoustic model through model reconstruction. To avoid model confusion, auxiliary decision trees are established for triphone PCPM. The acoustic model reconstruction on triphones is equivalent to decision tree merging. The effectiveness of this approach is evaluated on the 1997 Hub4NE Mandarin Broadcast News Corpus (1997 MBN) with different styles of speech. It gives a significant 2.39% absolute syllable error rate reduction in spontaneous speech.

关键词： Hidden Markov models Decision trees Merging Error analysis Humans natural languages Speech recognition Broadcasting Speech analysis Computational efficiency

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Script to speech conversion for Marathi language

Script to speech conversion for Marathi language

引用

IEEE Region 10 international conference TENCON

作者： N.B. Pasalkar C.V. Joshi M. Tasgaonkar Government College of Engineering Pune India

This paper investigates the method for "Devnagari script to speech conversion" as applied to Marathi language by developing the appropriate software. Pre-processing of the typed text is done. The neural network does the pattern matching and character recognition. Neural networks learn from examples and are fault tolerant. Output of neural network is recognized character. The dictionary of .wav files is prepared. After combining the recognised characters they are matched with the words in the .wav file. If the match occurs the success rate is 100% or otherwise the approach of forming the characters is adopted. Using sound playing functions the recognized words are played.

关键词： Speech natural languages Character recognition Optical character recognition software Biological neural networks Dictionaries Histograms Neural networks Tail Optical sensors

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Automatic language acquisition by an autonomous robot

Automatic language acquisition by an autonomous robot

引用

international Joint conference on Neural Networks (IJCNN)

作者： S. Levinson Weiyu Zhu Danfeng Li K. Squire Ruei-sung Lin M. Kleffner M. McClain J. Lee Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign Urbana IL USA

There is no such thing as a disembodied mind. We posit that cognitive development can only occur through interaction with the physical world. To this end, we are developing a robotic platform for the purpose of studying cognition. We suggest that the central component of cognition is a memory which is primarily associative, one where learning occurs as the correlation of events from diverse inputs. We also posit that human-like cognition requires a well-integrated sensory-motor system, to provide these diverse inputs. As implemented in our robot, this system includes binaural hearing, stereo vision, tactile sense, and basic proprioceptive control. On top of these abilities, we are implementing and studying various models of processing, learning and decision making. Our goal is to produce a robot that will learn to carry out simple tasks in response to natural language requests. The robot's understanding of language will be learned concurrently with its other cognitive abilities. We have already developed a robust system and conducted a number or experiments on the way to this goal, some details of which appear in this paper. This is a first progress report of what we believe will be a long term project with significant implications.

关键词： Robotics and automation Cognitive robotics Robot sensing systems Cognition Robot vision systems Auditory system Stereo vision Control systems Decision making natural languages

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Extracting biochemical interactions from MEDLINE using a link grammar parser

Extracting biochemical interactions from MEDLINE using a lin...

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international conference on Tools for Artificial Intelligence (ICTAI)

作者： Jing Ding D. Berleant Jun Xu A.W. Fulmer Department of Electrical and Computer Engineering Iowa State University Ames IA USA Procter and Gamble Company Cincinnati OH USA

Many natural language processing approaches at various complexity levels have been reported for extracting biochemical interactions from MEDLINE. While some algorithms using simple template matching are unable to deal with the complex syntactic structures, others exploiting sophisticated parsing techniques are hindered by greater computational cost. This study investigates link grammar parsing for extracting biochemical interactions. Link grammar parsing can handle many syntactic structures and is computationally relatively efficient. We experimented on a sample MEDLINE corpus. Although the parser was originally developed for conversational English and made many mistakes in parsing sentences from the biochemical domain, it nevertheless achieved better overall performance than a co-occurrence-only method. Customizing the parser for the biomedical domain is expected to improve its performance further.

关键词： Proteins Computational complexity Abstracts natural language processing Amino acids Insulin Computational efficiency Biomedical computing Databases Humans

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Bilingual speech recognition of Slovenian and Croatian weather forecasts

Bilingual speech recognition of Slovenian and Croatian weath...

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IEEE Region 8 international Symposium on Video/Image processing and Multimedia Communications (EURASIP)

作者： J. Zibert S. Martincic-Ipsic I. Ipsic F. Mihelic Faculty of Electrical Engineering University of Ljubljana Slovenia Faculty of Philosophy University of Rijeka Croatia

In the paper we present some results of a joint project in speech data collection and speech recognition of Slovenian and Croatian weather forecasts. In the paper we describe the procedures we have performed in order to obtain domain specific speech databases from broadcast programmes. We further describe the speech recognition experiments for language identification and the speech recognition experiments of monolingual and bilingual speech.

关键词： Weather forecasting Speech recognition Speech processing natural languages Multimedia communication Radio broadcasting Image databases Load forecasting Data acquisition TV broadcasting

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Unsupervised context sensitive language acquisition from a large corpus 03

Unsupervised context sensitive language acquisition from a l...

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Proceedings of the 17th international conference on Neural Information processing Systems

作者： Zach Solan David Horn Eytan Ruppin Shimon Edelman Sackler Faculty of Exact Sciences Tel Aviv University Tel Aviv Israel Department of Psychology Cornell University Ithaca NY

We describe a pattern acquisition algorithm that learns, in an unsupervised fashion, a streamlined representation of linguistic structures from a plain natural-language corpus. This paper addresses the issues of learning structured knowledge from a large-scale natural language data set, and of generalization to unseen text. The implemented algorithm represents sentences as paths on a graph whose vertices are words (or parts of words). Significant patterns, determined by recursive context-sensitive statistical inference, form new vertices. Linguistic constructions are represented by trees composed of significant patterns and their associated equivalence classes. An input module allows the algorithm to be subjected to a standard test of English as a Second language (ESL) proficiency. The results are encouraging: the model attains a level of performance considered to be "intermediate" for 9th-grade students, despite having been trained on a corpus (CHILDES) containing transcribed speech of parents directed to small children.

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Phonetic speaker recognition using maximum-likelihood binary-decision tree models

Phonetic speaker recognition using maximum-likelihood binary...

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international conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： J. Navratil Qin Jin W.D. Andrews J.P. Campbell IBM Thomas J. Watson Research Center Yorktown Heights NY USA Carnegie Mellon University Pittsburgh PA USA Department of Defense Fort Meade MD USA MIT Lincoln Laboratories Lexington MA USA

Recent work in phonetic speaker recognition has shown that modeling phone sequences using n-grams is a viable and effective approach to speaker recognition, primarily aiming at capturing speaker-dependent pronunciation and also word usage. The paper describes a method involving binary-tree-structured statistical models for extending the phonetic context beyond that of standard n-grams (particularly bigrams) by exploiting statistical dependencies within a longer sequence window without exponentially increasing the model complexity, as is the case with n-grams. Two ways of dealing with data sparsity are also studied; namely, model adaptation and a recursive bottom-up smoothing of symbol distributions. Results obtained under a variety of experimental conditions using the NIST 2001 Speaker Recognition Extended Data Task indicate consistent improvements in equal-error rate performance as compared to standard bigram models. The described approach confirms the relevance of long phonetic context in phonetic speaker recognition and represents an intermediate stage between short phone context and word-level modeling without the need for any lexical knowledge, which suggests its language independence.

关键词： Speaker recognition Context modeling Smoothing methods Loudspeakers natural languages Training data Laboratories Adaptation model NIST Automatic speech recognition

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Domain Ontology and Top-level Ontology:How can we co-ordinate the two?

Domain Ontology and Top-level Ontology:How can we co-ordinat...

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2003 international conference on natural language processing and knowledge engineering

作者： Jun-ichi Tsujii Department of Computer Science University of Tokyo

In this paper,we will discuss a specific domain ontology,GENIA ontology,which consists of 32 semantic categories in life science *** domain ontology is established to annotate papers in the field semantically,and has been use to annotate 2000 abstracts(around 500.000 words).The ontology is now being extended to cover other semantic categories like diseases,symptoms of diseases,body parts,*** categories that are not the major ones in the genome science field but. nonetheless frequently appear in papers of the *** order to extend the GENIA ontology to cover these categories,we have exploited existing domain ontologies like UMLS and the GENE *** effort is a typical example of ontology mapping among domain ontologies constructed by different groups of domain *** next crucial extension of the GENIA ontology is to cover concepts related with events,which involves mappings of verb subcategorization frames with distinct events of the *** assume that the mapping will be n to n and that the event ontology will require much finer semantic distinctions than those of verb subcategorization frames or distinctions of a general *** are particularly interested in how we can use the general ontology of events to accelerate acquisition of event ontology specific to the domain.

关键词： Ontology Domain Ontology and Top-level Ontology:How can we co-ordinate the two

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Keyword proximity search on XML graphs

Keyword proximity search on XML graphs

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international conference on Data engineering

作者： V. Hristidis Y. Papakonstantinou A. Balmin Computer Science and Engineering Department University of California San Diego USA

XKeyword provides efficient keyword proximity queries on large XML graph databases. A query is simply a list of keywords and does not require any schema or query language knowledge for its formulation. XKeyword is built on a relational database and, hence, can accommodate very large graphs. Query evaluation is optimized by using the graph's schema. In particular, XKeyword consists of two stages. In the preprocessing stage a set of keyword indices are built along with indexed path relations that describe particular patterns of paths in the graph. In the query processing stage plans are developed that use a near optimal set of path relations to efficiently locate the keyword query results. The results are presented graphically using the novel idea of interactive result graphs, which are populated on-demand according to the user's navigation and allow efficient information discovery. We provide theoretical and experimental points for the selection of the appropriate set of precomputed path relations. We also propose and experimentally evaluate algorithms to minimize the number of queries sent to the database to output the top-K results.

关键词： XML Database languages Video recording Tree graphs Relational databases Query processing Keyword search Search engines TV

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