Combining syntactical and statistical language constraints in context-dependent language models for interactive speech applications

Kiss, Imre; Kapanen, Pekka

doi:10.21437/eurospeech.1999-483

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Cited by 11 publications

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New Encoding Algorithm for Distributed Speech Recognition Based on DTFS Transform

Touazi

Debyeche

2012

Lecture Notes in Computer Science

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Abstract. The paper presents a new algorithm for efficient compression of front-end feature extracted parameters used in distributed speech recognition systems (DSR). In the proposed method the source encoder is mainly based on discrete time Fourier series (DTFS) by interpolation using Fourier coefficients with conventional vector quantization. The system provides a compression bit rate as low as 4 kbps; the experiments were carried out on the TIDigits Aurora2 database [1]. The simulation results show good recognition performance without dramatic change comparing with ETSI STQ-AURORA standard front-end feature compression algorithm with quantized features at 4.4 kbps [2].

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