Harmony perception by periodicity detection
نویسندگان
چکیده
منابع مشابه
Harmony Perception by Periodicity Detection
The perception of consonance/dissonance of musical harmonies is strongly correlated with their periodicity. This is shown in this article by consistently applying recent results from psychophysics and neuroacoustics, namely that the just noticeable difference between pitches for humans is about 1% for the musically important low frequency range and that periodicities of complex chords can be de...
متن کاملA Periodicity-based Theory for Harmony Perception and Scales
Empirical results demonstrate, that human subjects rate harmonies, e.g. major and minor triads, differently with respect to their sonority. These judgements of listeners have a strong psychophysical basis. Therefore, harmony perception often is explained by the notions of dissonance and tension, computing the consonance of one or two intervals. In this paper, a theory on harmony perception base...
متن کاملPeriodicity and pitch perception.
There has been experimental evidence pointing to at least two pitch mechanisms, the first involving low-order harmonics that are resolved along the basilar membrane, and the second a periodicity mechanism that depends only on the repetition rate of the time waveform on the basilar membrane. If this time waveform is derived from repeated bursts of sinusoidal tone, the second mechanism might be t...
متن کاملCircle detection by Harmony Search Optimization
Automatic circle detection in digital images has received considerable attention over the last years in computer vision as several efforts have aimed for an optimal circle detector. This paper presents an algorithm for automatic detection of circular shapes that considers the overall process as an optimization problem. The approach is based on the Harmony Search Algorithm (HSA), a derivative fr...
متن کاملWavelet periodicity detection algorithms
This paper deals with the analysis of time series with respect to certain known periodicities. In particular, we shall present a fast method aimed at detecting periodic behavior inherent in noisy data. The method is composed of three steps: 1. Non–noisy data are analyzed through spectral and wavelet methods to extract specific periodic patterns of interest. 2. Using these patterns, we construct...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Mathematics and Music
سال: 2015
ISSN: 1745-9737,1745-9745
DOI: 10.1080/17459737.2015.1033024