Journal ArticleDOI
The SIFT algorithm for fundamental frequency estimation
TLDR
It is demonstrated that the simplified inverse filter tracking algorithm (hereafter referred to as the SIFT algorithm) encompasses the desirable properties of both autocorrelation and cepstral pitch analysis techniques.Abstract:
In this paper a new method for estimating F 0 , the fundamental frequency of voiced speech versus time, is presented. The algorithm is based upon a simplified version of a general technique for fundamental frequency extraction using digital inverse filtering. It is demonstrated that the simplified inverse filter tracking algorithm (hereafter referred to as the SIFT algorithm) encompasses the desirable properties of both autocorrelation and cepstral pitch analysis techniques. In addition, the SIFT algorithm is composed of only a relatively small number of elementary arithmetic operations. In machine language, SIFT should run in several times real time while with special-purpose hardware it could easily be realized in real time.read more
Citations
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Journal ArticleDOI
Enhancement and bandwidth compression of noisy speech
Jae Lim,Alan V. Oppenheim +1 more
TL;DR: An overview of the variety of techniques that have been proposed for enhancement and bandwidth compression of speech degraded by additive background noise is provided to suggest a unifying framework in terms of which the relationships between these systems is more visible and which hopefully provides a structure which will suggest fruitful directions for further research.
Journal ArticleDOI
A comparative performance study of several pitch detection algorithms
TL;DR: A comparative performance study of seven pitch detection algorithms was conducted, consisting of eight utterances spoken by three males, three females, and one child, to assess their relative performance as a function of recording condition, and pitch range of the various speakers.
Journal ArticleDOI
On the use of autocorrelation analysis for pitch detection
TL;DR: Several types of (nonlinear) preprocessing which can be used to effectively spectrally flatten the speech signal are presented and an algorithm for adaptively choosing a frame size for an autocorrelation pitch analysis is discussed.
Journal ArticleDOI
Average magnitude difference function pitch extractor
TL;DR: The implementation of the AMDF pitch extractor (nonreal-time simulation and real-time) is described and experimental results presented to illustrate its basic measurement properties.
Journal ArticleDOI
A pattern recognition approach to voiced-unvoiced-silence classification with applications to speech recognition
TL;DR: A pattern recognition approach for deciding whether a given segment of a speech signal should be classified as voiced speech, unvoiced speech, or silence, based on measurements made on the signal, which has been found to provide reliable classification with speech segments as short as 10 ms.
References
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Journal ArticleDOI
Cepstrum Pitch Determination
TL;DR: Algorithms were developed heuristically for picking those peaks corresponding to voiced‐speech segments and the vocal pitch periods, which were then used to derive the excitation for a computer‐simulated channel vocoder.
Journal ArticleDOI
System for automatic formant analysis of voiced speech.
TL;DR: A system for automatically estimating the lowest three formants and the pitch period of voiced speech is presented, based on a digital computation of the cepstrum (defined as the inverse transform of the log magnitude of the z‐transform).
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Short‐Time Spectrum and “Cepstrum” Techniques for Vocal‐Pitch Detection
TL;DR: Cepstral techniques appear to be even more reliable and efficient than visual methods for pitch detection, and to produce high‐resolution spectra without utilizing either heterodyning methods or bandpass filter banks.
Journal ArticleDOI
Vocoders: Analysis and synthesis of speech
TL;DR: Techniques for analysis and synthesis of speech signals are reviewed with emphasis on vocoders and related devices for more efficient transmission and storage of speech.
Journal ArticleDOI
Parameter estimation in speech: A lesson in unorthodoxy
TL;DR: This experience in speech processing should serve as a reminder that a thorough understanding of the signal is paramount for successful analyses of real-world processes.