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Journal ArticleDOI

Separation of speech from interfering speech by means of harmonic selection

Thomas W. Parsons
- 01 Oct 1976 - 
- Vol. 60, Iss: 4, pp 911-918
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TLDR
In this paper, the harmonics of the desired voice in the Fourier transform of the input were selected to distinguish between two different voices. But the authors focus on the principal subproblem, the separation of vocalic speech.
Abstract
A common type of interference in speech transmission is that caused by the speech of a competing talker. Although the brain is adept at clarifying such speech, it relies heavily on binaural data. When voices interfere over a single channel, separation is much more difficult and intelligibility suffers. Clarifying such speech is a complex and varied problem whose nature changes with the moment‐to‐moment variation in the types of sound which interfere. This paper describes an attack on the principal subproblem, the separation of vocalic speech. Separation is done by selecting the harmonics of the desired voice in the Fourier transform of the input. In implementing this process, techniques have been developed for resolving overlapping spectrum components, for determining pitches of both talkers, and for assuring consistent separation. These techniques are described, their performance on test utterances is summarized, and the possibility of using this process as a basis for the solution of the general two‐tal...

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Citations
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Patent

Systems and methods for multiple pitch tracking using a multidimensional function and strength values

TL;DR: In this paper, a function module, a strength module, and a filter module are used to extract the pitch of the component from the input signal based on the strength of the first extremum.
Dissertation

Exploiting primitive grouping constraints for noise robust automatic speech recognition : studies with simultaneous speech

André Coy
TL;DR: An approach to developing a speech recognition system that takes inspiration from the approach of human speech recognition is presented.
Proceedings ArticleDOI

Pitch-aided spectral estimation for noise-robust speech recognition

A. Erell, +1 more
TL;DR: A method for utilizing the quasi-periodicity of speech in a minimum-mean-square-error (MMSE) estimation of the DFT log-amplitude, either for speech enhancement or for noise-robust speech recognition, is described.
Proceedings ArticleDOI

Phoneme adjustment in enhanced speech

TL;DR: In this paper, the amplitude spectrum of voiced regions of speech is smoothed in order to reduce the effects of noise and the number of harmonics/peaks used for reconstruction varied from 40 to 50 in each frame of 256 DFT points and the reconstructed speech has much better subjective quality and improved signal/noise ratio.
Journal ArticleDOI

A novel optimization based method for separation of periodic signals

TL;DR: Tests show that the proposed method for separating the individual periodic components of a mixed signal is more robust than the matrix algebraic separation (MAS) system in the case of a slightly frequency-modulated test signal.