Book ChapterDOI
Fundamental Frequency Estimation
John D. Markel,Augustine H. GrayJr. +1 more
- pp 190-211
Reads0
Chats0
TLDR
The fundamental frequency (F0) is the rate at which glottal volume velocity pulses are applied to the vocal tract, i.e., the driving function to the model is periodic with a period of 1/F0.Abstract:
The fundamental frequency (F0) is a basic parameter in acoustical studies of speech. It is also a necessary parameter for low bit rate speech coding systems. It is generally considered to be one of the acoustical correlates to the perceived intonation pattern of speech. If the fundamental frequency of a speaker is constant, the speech would be perceived as being machine-like or monotone. If the speaker is excited, the fundamental frequency generally increases. It is the acoustical correlate to the rate at which the vocal folds open and close (or vibrate). If the folds are vibrating rapidly, a high fundamental frequency will be measured. In the linear speech production model, the fundamental frequency is the rate at which glottal volume velocity pulses are applied to the vocal tract, i.e., the driving function to the model is periodic with a period of 1/F0.read more
Citations
More filters
High quality voice transformations based on modeling radiated voice pulses in frequency domain
TL;DR: This approach tries to combine the strengths of classical time and frequency domain techniques into a single framework, providing both an independent control of each voice pulse and flexible timbre and phase modification capabilities.
Proceedings ArticleDOI
Real-time Melodic Accompaniment System for Indian Music Using TMS320C6713
Prateek Verma,Preeti Rao +1 more
TL;DR: An instrumental accompaniment system for Indian classical vocal music is designed and implemented on a Texas Instruments Digital Signal Processor TMS320C6713, which will act as a virtual accompanist following the main artist, possibly a vocalist.
Journal ArticleDOI
Adaptive Method for Measuring a Fundamental Tone Frequency Using a Two-Level Autoregressive Model of Speech Signals
Proceedings ArticleDOI
PCG signal analysis using teager energy operator & autocorrelation function
TL;DR: Teager energy operator and autocorrelation function are investigated to analyze the PCG signal and extract different parameters such as S1-Systole and S2-Diastole signals their timing, and heart rate estimation.
Dissertation
An HMM-based automatic singing transcription platform for a sight-singing tutor
TL;DR: The aim in introducing context-dependency is to improve transition region modeling, which in turn should increase note transcription accuracy, but also improve the time-alignment of the notes and the transition regions.