A modified low roundoff digital oscillator design

The work of this thesis is to summarize and compares the existing digital oscillator design methods and combine them to form a modified structure for oscillator design. First of all, a combined structure of complex oscillator design is proposed. The structure combines the advantages of low hardware complexity and low roundoff errors. Then based on the suggested complex oscillator structure, some new digital oscillator structures with uniform frequency spacing are suggested. The new structures are also the modified structure of the existing oscillator. By adding power-of-two shift boxes into the modified structure, dynamic range of the output is enlarged and the quantization errors are greatly reduced. The modified oscillators can generate low frequency and low amplitude sinusoid waves with very small phase and amplitude deviation. In order to further reduce the quantization errors, error feedback circuits is applied into the circuit to further reduce the errors

ARTIFICIAL INTELLIGENCE-BASED APPROACH TO MODELLING OF PIPE ORGANS

The aim of the project was to develop a new Artificial Intelligence-based method to aid modeling of musical instruments and sound design. Despite significant advances in music technology, sound design and synthesis of complex musical instruments is still time consuming, error prone and requires expert understanding of the instrument attributes and significant expertise to produce high quality synthesised sounds to meet the needs of musicians and musical instrument builders. Artificial Intelligence (Al) offers an effective means of capturing this expertise and for handling the imprecision and uncertainty inherent in audio knowledge and data. This thesis presents new techniques to capture and exploit audio expertise, following extended knowledge elicitation with two renowned music technologist/audio experts, developed and embodied into an intelligent audio system. The Al combined with perceptual auditory modeling ba.sed techniques (ITU-R BS 1387) make a generic modeling framework providing a robust methodology for sound synthesis parameters optimisation with objective prediction of sound synthesis quality. The evaluation, carried out using typical pipe organ sounds, has shown that the intelligent audio system can automatically design sounds judged by the experts to be of very good quality, while significantly reducing the expert's work-load by up to a factor of three and need for extensive subjective tests. This research work, the first initiative to capture explicitly knowledge from audio experts for sound design, represents an important contribution for future design of electronic musical instruments based on perceptual sound quality will help to develop a new sound quality index for benchmarking sound synthesis techniques and serve as a research framework for modeling of a wide range of musical instruments.Musicom Lt