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This thesis details research carried out in the through-water data communication field. An overview of the phenomena that prohibit acoustic communication in long-range shallow-water channels is constructed. Background research found that robust communications has not been achieved using single receiver reception in this environment. This work investigates the modulation technique itself and aims to improve on existing schemes (that have been applied to this environment). This is achieved with innovative techniques, based on multiple-frequency-shift-keying (MFSK) and space-frequency-shift-keying (SFSK). A number of industrial specified restrictions are placed on this work, including bandwidth restriction. Novel ways of intrinsically transmitting synchronisation information are therefore implemented. The development of appropriate systems is covered with general and platform specific implementation strategies being covered. A single modulation scheme (the three-chip four-frequency-shift-keying, 3C4FSK, scheme) has been put forward for consideration in any future research. Practical lab-based tests and the mathematical analysis is detailed. Conclusions recommend further funding of long-range shallow sea-water trails of the 3C4FSK scheme and for the industrial scope of this work to allow investigation into multiple receiver systems that allow spatial processing of the signal as these schemes have been shown lately to have potential in long-range channels.

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The aim of this research is to demonstrate the significance of signal phase content in time localization issues in synthetic signals and in the extraction of appropriate features from acoustically similar audio recordings (non-synthetic signals) for audio classification purposes. Published work, relating to audio classification, tends to be1 focused on the discrimination of audio classes that are dissimilar acoustically. Consequently, a wide range of features, extracted from the audio recordings, has been appropriate for the classification task. In this research, the audio classification application involves audio recordings (digitized through the same pre-processing conditions) that are acoustically similar and hence, only a few features are appropriate, due to the similarity amongst the classes. The difficulties in processing the phase spectrum of a signal have probably led previous researchers to avoid its investigation. In this research, the sources of these difficulties are studied and certain methods are employed to overcome them. Subsequently, the phase content of the signal has been found to be useful for various applications. The justification of this, is demonstrated via audio classification (non-synthetic signals) and time localization (synthetic signals) applications. Summarizing, the original contributions, introduced based on this research work, are the 'whitened' Hartley spectrum and its short-time analysis, as well as the use of the Hartley phase cepstrum as a time localization tool and the use of phase related feature vectors for the audio classification application.

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This thesis presents the theory, implementation and applications of the harmonic sinusoid modeling of pitched audio events. Harmonic sinusoid modeling is a parametric model that expresses an audio signal, or part of an audio signal, as the linear combination of concurrent slow-varying sinusoids, grouped together under harmonic frequency constraints. The harmonic sinusoid modeling is an extension of the sinusoid modeling, with the additional frequency constraints so that it is capable to directly model tonal sounds. This enables applications such as object-oriented audio manipulations, polyphonic transcription, instrument/singer recognition with background music, etc. The modeling system consists of an analyzer and a synthesizer. The analyzer extracts harmonic sinusoidal parameters from an audio waveform, while the synthesizer rebuilds an audio waveform from these parameters. Parameter estimation is based on a detecting-grouping-tracking framework. The detecting stage finds and estimates sinusoid atoms; the grouping stage collects concurrent atoms into harmonic groups; the tracking stage collects the atom groups at different time to form continuous harmonic sinusoid tracks. Compared to standard sinusoid model, the harmonic model focuses on harmonic groups of atoms rather than on isolated atoms, therefore naturally represents tonal sounds. The synthesizer rebuilds the audio signal by interpolating measured parameters along the found tracks. We propose the first application of the harmonic sinusoid model in digital audio editors. For audio editing, with the tonal events directly represented by a parametric model, we can implement standard audio editing functionalities on tonal events embedded in an audio signal, or invent new sound effects based on the model parameters themselves. Possibilities for other applications are suggested at the end of this thesis.