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Download e-book for iPad: Advanced Algorithms and Architectures for Speech by Giancarlo Pirani (auth.), Giancarlo Pirani (eds.)

By Giancarlo Pirani (auth.), Giancarlo Pirani (eds.)

This publication is meant to provide an summary of the most important effects completed within the box of average speech figuring out within ESPRIT undertaking P. 26, "Advanced Algorithms and Architectures for Speech and photograph Processing". The venture all started as a Pilot undertaking within the early degree of section 1 of the ESPRIT application introduced by means of the fee of the ecu groups. After 365 days, within the mild of the initial effects that have been got, it used to be proven for its 5-year length. although the actions have been performed for either speech and snapshot comprehend­ ing we hottest to concentration the remedy of the booklet at the first quarter which crystallized usually round the CSELT crew, with the precious cooperation of AEG, Thomson-CSF, and Politecnico di Torino. as a result of the paintings of the 5 years of the undertaking, the Consortium was once capable of improve an exact and entire figuring out procedure that is going from a consistently spoken average language sentence to its which means and the resultant entry to a database. once we all started in 1983 we had a few services in small-vocabulary syntax-driven connected-word speech popularity utilizing Hidden Markov types, in written ordinary lan­ guage knowing, and in layout almost always established upon bit-slice microprocessors.

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Additional info for Advanced Algorithms and Architectures for Speech Understanding

Example text

Several representations of words have been devised and experimented with that rely on different models and codes for accessing the lexicon. All models, however, describe words through a level of representation corresponding to phonemes. This assumption is also implicit in models like LAFS [28], where words are described as sequences of diphone spectral templates, and an acoustic code is the basis of the lexical access. According to most of these models, words are recognized by means of a single-step matching strategy that use all available acoustic-phonetic information.

For instance in Italian, the letter s is sometimes pronounced as the phoneme /s/ and sometimes as the phoneme /z/ depending on the speaker provenience. In those cases we introduced multiple transcriptions of the same word; for example, the Italian word CASA (house) has two phonetic transcriptions that are /lcaza/ and /lcasa/. 2 along with the IPA (International Phonetic Alphabet) symbols. Also, a semicolon (;) following a consonant means that consonant is a geminate cluster, like , /t/ in the word OTTO (eight, /ot; o/).

This operation would be more complex and expensive if performed on a graph. Given the micro-segmentation of an uttered word belonging to a lexicon represented by a tree TN, lexical access is performed by detecting the- sequences of phonetic nodes TN(i), and hence the corresponding words, whose costs computed by means of the 3DP lie within a fixed range of the best one. e. the nodes sharing the same father, and LEQW is the (possible empty) list of words that share the same path from the root node TN(O) to TN(i).

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