A versatile pitch tracking algorithm: from human speech to killer whale vocalizations.
نویسندگان
چکیده
In this article, a pitch tracking algorithm [named discrete logarithmic Fourier transformation-pitch detection algorithm (DLFT-PDA)], originally designed for human telephone speech, was modified for killer whale vocalizations. The multiple frequency components of some of these vocalizations demand a spectral (rather than temporal) approach to pitch tracking. The DLFT-PDA algorithm derives reliable estimations of pitch and the temporal change of pitch from the harmonic structure of the vocal signal. Scores from both estimations are combined in a dynamic programming search to find a smooth pitch track. The algorithm is capable of tracking killer whale calls that contain simultaneous low and high frequency components and compares favorably across most signal to noise ratio ranges to the peak-picking and sidewinder algorithms that have been used for tracking killer whale vocalizations previously.
منابع مشابه
Voice transformations: from speech synthesis to mammalian vocalizations
This paper describes a phase vocoder based technique for voice transformation. This method provides a flexible way to manipulate various aspects of the input signal, e.g., fundamental frequency of voicing, duration, energy, and formant positions, without explicit extraction. The modifications to the signal can be specific to any feature dimensions, and can vary dynamically over time. There are ...
متن کاملSegmentation of Killer Whale Vocalizations Using the Hilbert-Huang Transform
The study of cetacean vocalizations is usually based on spectrogram analysis. The feature extraction is obtained from 2D methods like the edge detection algorithm. Difficulties appear when signal-to-noise ratios are weak or when more than one vocalization is simultaneously emitted. This is the case for acoustic observations in a natural environment and especially for the killer whales which swi...
متن کاملAutomatic classification of killer whale vocalizations using dynamic time warping.
A set of killer whale sounds from Marineland were recently classified automatically [Brown et al., J. Acoust. Soc. Am. 119, EL34-EL40 (2006)] into call types using dynamic time warping (DTW), multidimensional scaling, and kmeans clustering to give near-perfect agreement with a perceptual classification. Here the effectiveness of four DTW algorithms on a larger and much more challenging set of c...
متن کاملCharacterizing the graded structure of false killer whale (Pseudorca crassidens) vocalizations.
The vocalizations from two, captive false killer whales (Pseudorca crassidens) were analyzed. The structure of the vocalizations was best modeled as lying along a continuum with trains of discrete, exponentially damped sinusoidal pulses at one end and continuous sinusoidal signals at the other end. Pulse trains were graded as a function of the interval between pulses where the minimum interval ...
متن کاملThe neural network classification of false killer whale (Pseudorca crassidens) vocalizations.
This study reports the use of unsupervised, self-organizing neural network to categorize the repertoire of false killer whale vocalizations. Self-organizing networks are capable of detecting patterns in their input and partitioning those patterns into categories without requiring that the number or types of categories be predefined. The inputs for the neural networks were two-dimensional charac...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- The Journal of the Acoustical Society of America
دوره 126 1 شماره
صفحات -
تاریخ انتشار 2009