An embedded sinusoidal transform codec with measured phases and sampling rate scalability

Aguilar, Gualberto; Chen, Juin-Hwey; Dunn, Robert B.; McAulay, R.; Sun, Xiaoqin; Wang, Wei; Zopf, Robert

doi:10.1109/icassp.2000.859166

Cited by 5 publications

(1 citation statement)

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“…Furthermore, small footprint implementations suitable for low-end terminals like handheld devices may require further compression. A typical approach is to quantize only the phases of the first harmonics [19], [20] which define the coarse shape of the waveform. Another approach is to fit the unwrapped phases to a sinusoidal basis [21].…”

Section: Introductionmentioning

confidence: 99%

Wrapped Gaussian Mixture Models for Modeling and High-Rate Quantization of Phase Data of Speech

Agiomyrgiannakis

Stylianou

2009

IEEE Trans. Audio Speech Lang. Process.

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Abstract-The harmonic representation of speech signals has found many applications in speech processing. This paper presents a novel statistical approach to model the behavior of harmonic phases. Phase information is decomposed into three parts: a minimum phase part, a translation term, and a residual term referred to as dispersion phase. Dispersion phases are modeled by wrapped Gaussian mixture models (WGMMs) using an expectation-maximization algorithm suitable for circular vector data. A multivariate WGMM-based phase quantizer is then proposed and constructed using novel scalar quantizers for circular random variables. The proposed phase modeling and quantization scheme is evaluated in the context of a narrowband harmonic representation of speech. Results indicate that it is possible to construct a variable-rate harmonic codec that is equivalent to iLBC at approximately 13 kbps.Index Terms-Circular statistics, , phase quantization, sinusoidal models, speech analysis, speech coding, voice-over-IP, wrapped Gaussian mixture models (WGMMs).

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Section: Introductionmentioning

confidence: 99%