Titlebook: Searching Speech Databases; Features, Techniques Leena Mary,Deekshitha G Book 2019 The Author(s), under exclusive licence to Springer Natur

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书目名称Searching Speech Databases影响因子(影响力)




书目名称Searching Speech Databases影响因子(影响力)学科排名




书目名称Searching Speech Databases网络公开度




书目名称Searching Speech Databases网络公开度学科排名




书目名称Searching Speech Databases被引频次




书目名称Searching Speech Databases被引频次学科排名




书目名称Searching Speech Databases年度引用




书目名称Searching Speech Databases年度引用学科排名




书目名称Searching Speech Databases读者反馈




书目名称Searching Speech Databases读者反馈学科排名

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inserted DNA fragments and with prokaryotic DNA the yield of gene products may thus be enhanced. The recombinant phages can, of course, be further manipulated themselves to improve yields of DNA or of gene products, or to facilitate the analysis of cloned DNA sequences.

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Book 2019 examine different features, techniques and evaluation measures attempted by researchers around the world. The topics covered also include available databases, software / tools, patents / copyrights, and different platforms for benchmarking. The content is relevant for developers, academics, and stu

FELON

Audio Search Techniques, smart phones and are always using multimedia data. A large amount of multimedia data resources are freely available nowadays. But, any resource will become useful, only if it can be handled efficiently. A huge amount of audio archives are available in different websites. Different audio archives in

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FLAIL

Features, Representations, and Matching Techniques for Audio Search,Coefficients (MFCC), Fourier–Bessel Coefficients (FBCC), Linear Prediction Cepstral Coefficients (LPCC), Perceptual LPCC, and Frequency Domain LP (FDP) are used as primary features for searching speech databases. Primary features are used for converting speech to representations such as seams, patch

范例

Keyword Spotting Techniques,pproaches have been implemented to do keyword spotting. Keyword spotting is considered to be the first among speech searching. Later, keyword spotting paved the way to Spoken Term Detection (STD) and Query by Example STD (QbE-STD). In the early days, researchers have used HMM for KWS, where the spee

BIDE

Spoken Term Detection Techniques,is is termed as Spoken Term Detection (STD). STD can be broadly classified into Text-based STD and Query by Example STD (QbE-STD). In normal STD, query as well as database is converted to corresponding text/symbol for searching purpose. Since this technique needs speech to text mapping, some form of

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