Titlebook: Automatic Speech Recognition on Mobile Devices and over Communication Networks; Zheng-Hua Tan,B?rge Lindberg Book 2008 Springer-Verlag Lon

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蒙太奇

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Calogero Guccio,Domenico Lisi,Ilde Rizzocreated to ensure interoperability between the feature extraction running on a client device and a compatible recogniser running on a remote server. They are intended for use in the implementation of commercial services for speech and multimodal services over mobile networks. In the process of devel

意見一致

Timo Kivist?,Veli Matti Virolainen and the work carried out by the ETSI Aurora group. Feature extraction is examined first and begins with a basic implementation of mel-frequency cepstral coefficients (MFCCs). Additional processing, in the form of noise and channel compensation, is explained and has the aim of increasing speech reco

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Calogero Guccio,Domenico Lisi,Ilde Rizzoreless or network communication channels within DSR systems are typically noisy and bursty. Thus, DSR systems must utilize efficient Error Recovery (ER) schemes during transmission of speech information. Some ER strategies, referred to as forward error control (FEC), aim to create redundancy in the

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Measurements of Purchasing Performanceunit cost for components produced in very large numbers (cell phones, set-top boxes). Both requirements are addressed by CPU’s with integer-only arithmetic units which motivate the fixed-point arithmetic implementation of automatic speech recognition (ASR) algorithms. Large vocabulary continuous spe