Voice Activity Detection Algorithm Based on Radial Basis Function Network(Fundamental Theories for Communications)

スポンサーリンク

概要

• 論文の詳細を見る

• This paper proposes a Voice Activity Detection (VAD) algorithm using Radial Basis Function (RBF) network. The k-means clustering and Least Mean Square (LMS) algorithm are used to update the RBF network to the underlying speech condition. The inputs for RBF are the three parameters a Code Excited Linear Prediction (CELP) coder, which works stably under various background noise levels. Adaptive hangover threshold applies in RBF-VAD for reducing error, because threshold value has trade off effect in VAD decision. The experimental results show that the proposed VAD algorithm achieves better performance than G.729 Annex B at any noise level.

• 2005-04-01

著者

• KIM Hong

  Division of Electrical and Computer Engineering, Hanyang University

• PARK Sung

  Division of Electrical and Computer Engineering, Hanyang University

• Park Sung‐kwon

  Hanyang Univ. Kor

• Kim Hong

  Division Of Electrical And Computer Engineering Hanyang University

関連論文

• Voice Activity Detection Algorithm Based on Radial Basis Function Network(Fundamental Theories for Communications)
• Optimum UDP Packet Sizes in Ad Hoc Networks(Terrestrial Radio Communications)
• Cytoplasmic Localization of Jab1 and p27^ Might Be Associated with Invasiveness of Papillary Thyroid Carcinoma
• Genetic association analysis of TAP1 and TAP2 polymorphisms with aspirin exacerbated respiratory disease and its FEV1 decline
• A Case of Cystic Lymphocytic Hypophysitis with Cacosmia and Hypopituitarism
• Efficacy of intravenously administered ibandronate in postmenopausal Korean women with insufficient response to orally administered bisphosphonates

スポンサーリンク