Publication

A Simple Continuous Pitch Estimation Algorithm

Petr Motlicek, Philip Neil Garner
2013
Journal Articles

Abstract

Recent work in text to speech synthesis has pointed to the benefit of using a continuous pitch estimate; that is, one that records pitch even when voicing is not present. Such an approach typically requires interpolation. The purpose of this paper is to show that a continuous pitch estimation is available from a combination of otherwise well known techniques. Further, in the case of an autocorrelation based estimate, the continuous requirement negates the need for other heuristics to correct for common errors. An algorithm is suggested, illustrated, and demonstrated using a parametric vocoder.

Official source

https://infoscience.epfl.ch/entities/publication/ea59c6d6-3a57-4bd3-a9ac-769f572e9dd3

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Petr Motlicek, Philip Neil Garner
2013
Journal Articles

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/ea59c6d6-3a57-4bd3-a9ac-769f572e9dd3

About this result

Related concepts (28)

Spectral density estimation

In statistical signal processing, the goal of spectral density estimation (SDE) or simply spectral estimation is to estimate the spectral density (also known as the power spectral density) of a signal from a sequence of time samples of the signal. Intuitively speaking, the spectral density characterizes the frequency content of the signal. One purpose of estimating the spectral density is to detect any periodicities in the data, by observing peaks at the frequencies corresponding to these periodicities.

Autocorrelation

Autocorrelation, sometimes known as serial correlation in the discrete time case, is the correlation of a signal with a delayed copy of itself as a function of delay. Informally, it is the similarity between observations of a random variable as a function of the time lag between them. The analysis of autocorrelation is a mathematical tool for finding repeating patterns, such as the presence of a periodic signal obscured by noise, or identifying the missing fundamental frequency in a signal implied by its harmonic frequencies.

Speech synthesis

Speech synthesis is the artificial production of human speech. A computer system used for this purpose is called a speech synthesizer, and can be implemented in software or hardware products. A text-to-speech (TTS) system converts normal language text into speech; other systems render symbolic linguistic representations like phonetic transcriptions into speech. The reverse process is speech recognition. Synthesized speech can be created by concatenating pieces of recorded speech that are stored in a database.

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