Very Low Rate Scalable Speech Coding through Classified Embedded Matrix Quantization. (12th April 2010)

• Record Type: Journal Article
• Authors: Jahangiri Jahangiri, Ehsan Ehsan; Ghaemmaghami Ghaemmaghami, Shahrokh Shahrokh
• Other Names: Jensen Jensen Soren Soren Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2010(2010)
• Publication Date: 2010-04-12
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2010/480345
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : This paper proposes a scalable speech coding scheme using the embedded matrix quantization of the LSFs in the LPC model. For an efficient quantization of the spectral parameters, two types of codebooks of different sizes are designed and used to encode unvoiced and mixed voicing segments separately. The tree-like structured codebooks of our embedded quantizer, constructed through a cell merging process, help to make a fine-grain scalable speech coder. Using an efficient adaptive dual-band approximation of the LPC excitation, where voicing transition frequency is determined based on the concept of instantaneous frequency in the frequency domain, near natural sounding synthesized speech is achieved. Assessment results, including both overall quality and intelligibility scores show that the proposed coding scheme can be a reasonable choice for speech coding in low bandwidth communication applications.