Exploring the characteristics of analytic decomposition of speech signals

This paper investigates the properties of analytic transformation of speech into envelope and phase functions. The envelope is shown to evolve slowly with the pitch of the input speech, whilst the phase consists of two components; one evolving slowly with pitch and another that exhibits a more rapid evolution. We investigate decomposing the phase component further using two distinct methods: (a) filtering of the phase in the pitch evolutionary direction and (b) performing a second analytic decomposition of the phase into secondary envelope and phase components. To examine the characteristics of the pitch cycle evolution, the analytic transform is employed in a waveform interpolation (WI) coding structure. The two phase decompositions are then analysed with particular emphasis on quantisation sensitivity and the required transmission rate. Results indicate that the analytic decomposition may offer a degree of scalability to speech coders, especially when employed in coders that exploit pitch evolution such as WI

Low rate WI SEW representation using a REW-implicit pulse model

Reducing the bit rate of waveform interpolation speech coders while maintaining the perceptual quality has been the focus of a great deal of research. This letter proposes a new method of slowly evolving waveform (SEW) quantization specifically targeted at low rate coding. The proposed method uses a pulse model whose parameters are implicitly contained in the quantized rapidly evolving waveform (REW) parameters, thus requiring no bits for transmission. Results indicate no degradation in perceptual speech quality when compared to that of the existing SEW quantization method. This retention of perceptual quality is in spite of a 12% reduction in the overall coder bit rate

An analysis of the limitations of blind signal separation application with speech

Blind Signal Separation (BSS) techniques are commonly employed in the separation of speech signals, using Independent Component Analysis (ICA) as the criterion for separation. This paper investigates the viability of employing ICA for real-time speech separation (where short frame sizes are the norm). The relationship between the statistics of speech and the assumption of statistical independence (at the core of ICA) is examined over a range of frame sizes. The investigation confirms that statistical independence is not a valid assumption for speech when divided into the short frames appropriate to real-time separation. This is primarily due to the quasi-stationary nature of speech over the temporal short term. We conclude that employing ICA for real-time speech separation will always result in limited performance due to a fundamental failure to meet the strict assumptions of ICA

High-spin states in 232U investigated with the 232Th(α, 4nγ) reaction

The ground-state rotational band of 232U is established up to Iπ = 16+ (tentatively 18+) through a study of the 232Th(α, 4nγ) reaction. Conversion electron spectroscopy is found to be especially useful in circumventing the difficulties caused by strong fission competition

The Galactic positron flux and dark matter substructures

In this paper we calculate the Galactic positron flux from dark matter annihilation in the frame of supersymmetry, taking the enhancement of the flux by existence of dark matter substructures into account. The propagation of positrons in the Galactic magnetic field is solved in a realistic numerical model GALPROP. The secondary positron flux is recalculated in the GLAPROP model. The total positron flux from secondary products and dark matter annihilation can fit the HEAT data well when taking a cuspy density profile of the substructures.Comment: 16 pages, 10 figures, accepted by JCA