Download Evaluation of Text and Speech Systems (Text, Speech and by by Laila Dybkjaer (Editor), Holmer Hemsen (Editor), Wolfgang PDF

By by Laila Dybkjaer (Editor), Holmer Hemsen (Editor), Wolfgang Minker (Editor)

In its 9 chapters, this booklet presents an summary of the state of the art and top perform in different sub-fields of evaluate of textual content and speech platforms and parts. The assessment points lined comprise speech and speaker popularity, speech synthesis, lively conversing brokers, part-of-speech tagging, parsing, and average language software program like computing device translation, info retrieval, query answering, spoken discussion structures, info assets, and annotation schemes. With its huge assurance and unique contributions this booklet is exclusive within the box of overview of speech and language technology.This e-book is of specific relevance to complex undergraduate scholars, PhD scholars, educational and business researchers, and practitioners.

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Extra info for Evaluation of Text and Speech Systems (Text, Speech and Language Technology)

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Matsui, T. and Furui, S. (1994). Similarity Normalization Method for Speaker Verification Based on a Posteriori Probability. In Proceedings of the ESCA Workshop on Automatic Speaker Recognition, Identification and Verification, pages 59–62, Martigny, Switzerland. M¨oller, S. (2005). Quality of Telephone-Based Spoken Dialogue Systems. Springer, New York, USA. , and Wessel, F. (1997). Statistical Language Modeling Using Leaving-one-out. In Young, S. , editors, Corpusbased Methods in Language and Speech Processing, pages 174–207.

The alignment depends on the relative weights of the contributions of the three types of errors: substitutions, insertions, and deletions. Hunt (1990) discussed the theory of word–symbol alignment and analysed several experiments on alignment. Usually, the three types of errors have equal weights. Depending on the application, one can assign different weights to the various kinds of errors. 14) where NS , NI , and ND are the numbers of substitutions, insertions, and deletions, respectively. 15) Note that this error measure can become larger than 1 in cases of extremely bad recognition.

Transactions of IECE, 55-A, 1(10):549–556. , and Hori, C. (2004). Speech-to-text and Speech-to-speech Summarization of Spontaneous Speech. IEEE Transactions on Speech and Audio Processing, 12(4):401–408. Gales, M. J. F. and Young, S. J. (1993). HMM Recognition in Noise Using Parallel Model Combination. In Proceedings of the European Conference on Speech Communication and Technology (Eurospeech), volume 2, pages 837–840, Berlin, Germany. , editors (1998). Spoken Language System Assessment. Handbook of Standards and Resources for Spoken Language Systems, volume 3.

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