Journal ArticleDOI
Separation of speech from interfering speech by means of harmonic selection
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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...read more
Citations
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Journal ArticleDOI
Fusion of simultaneous tonal glides: The role of parallelness and simple frequency relations
Albert S. Bregman,Peter Doehring +1 more
TL;DR: Adult listeners heard a pure-tone glide (“captor”) repeatedly alternating with a complex glide consisting of three simultaneouspure-tone glides, which matched the captor glide in its frequency center, orientation, and direction.
Proceedings ArticleDOI
The GRASP sound separation system
TL;DR: The GRASP system (for Grouping Research on Auditory Sound Processing) is a part of that overall framework for sound separation and uses the physical cues present in the acoustic signal to decide how many sounds are present and of what each sound consists.
Book ChapterDOI
Multiple F0 Estimation
DeLiang Wang,Guy J. Brown +1 more
TL;DR: This chapter contains sections titled: Introduction Signal Models Single-Voice F 0 Estimation Multiple-VoiceF 0Estimation Issues Other Sources of Information Estimating the Number of Sources Evaluation Application Scenarios Conclusion
Journal ArticleDOI
A sound segregation algorithm for reverberant conditions
A. Shamsoddini,P. N. Denbigh +1 more
TL;DR: A system has been developed that enables a wanted speech signal to be extracted from a background of unwanted speech and other interference under real-life conditions using only two microphones 25 cm apart in a hybrid algorithm which takes advantages of both.
Journal ArticleDOI
Voice segregation by difference in fundamental frequency: evidence for harmonic cancellation.
TL;DR: Listeners' ability to use a difference of two semitones in fundamental frequency (F0) to segregate a target voice from harmonic complex tones, with speech-like spectral profiles, was investigated and F0-segregation was found to be independent of the depth of masker envelope modulations.