Comparative Analysis of Sound Synthesis Methods and Development of a Compact Analog Synthesizer

The significance of sound synthesis in music production is vital for generating different timbres and textures using various synthesis techniques. This study provides a comparison of various sound synthesis techniques (Additive, Subtractive, Frequency Modulation (FM), Wavetable, Granular, Physical Modeling based on the Karplus-Strong Algorithm, Sample-Based Synthesis) by creating digital implementations of each technique in Python and building an analog synthesizer to assess the implications of hardware-based synthesis. The findings indicate trade-offs among the techniques involving computational performance, spectral manipulation and realism in timbre generation. Additive synthesis produces precise harmonic control at the expense of high computation. Comparatively, subtractive synthesis is a more efficient process for harmonic shaping. FM synthesis offers an effective balance of efficiency and timbral richness, and wavetable synthesis is useful for real-time performance but has limited flexibility in the spectral domain. Similarly, granular synthesis provides an advanced method of pitch and time manipulation but requires careful tuning and doesn’t introduce artifacts. Physical modeling synthesis efficiently simulates plucked string instruments with a much lesser processing cost, but is limited in context. Sample-based synthesis can achieve a high degree of realism, but it depends on the quality and availability of recorded samples. Overall FM and wavetable synthesis have the best potential for real-time application because of their efficiency and timbral variety. This paper is innovative in its hybrid approach, by combining simulations of digitally sound synthesis in Python, and sound synthesis using a constructed analog synthesizer, it allows practical, comparative evaluation. Output audio was validated using both waveform analysis and subjective listening to ensure timbral fidelity. Efficiency and real time feasibility were evaluated through computational analysis and hardware performance criteria. The findings of this research could inform the development of efficient sound players, educational synthesis tools, and hybrid analog-digital synthesizers. Physical modeling and sample based synthesis could be more effective in the replication of realistic instruments. This study can guide practitioners in relation to identifying the best type of synthesis for either a computational constraint, spectral richness, or desired application for digital and analog sound design.