Learn More
A dual-microphone speech-signal enhancement algorithm, utilizing phase-error based filters that depend only on the phase of the signals, is proposed. This algorithm involves obtaining time-varying, or alternatively, time-frequency (TF), phase-error filters based on prior knowledge regarding the time difference of arrival (TDOA) of the speech source of(More)
This paper proposes a phase-based dual-microphone speech enhancement technique that utilizes a prior speech model. Recently, it has been shown that phase-based dual-microphone filters can result in significant noise reduction in low signal-to-noise ratio [(SNR) less than 10 dB] conditions and negligible distortion at high SNRs (greater than 10 dB), as long(More)
In this paper, we analyze the effects of uncertainty in the phase of speech signals on the word recognition error rate of human listeners. The motivating goal is to get a quantitative measure on the importance of phase in automatic speech recognition by studying the effects of phase uncertainty on human perception. Listening tests were conducted for 18(More)
A technique usingg the time-frequency phase information of two microphones is proposedd to estimate an ideal time-frequency maskk usingg time-delay-of-arrival (TDOA) of the signal of interest. At a signal-to-noise ratio (SNR) of 0dB, the proposedd technique usingg two microphones achieves a digit recognition rate (average over 55 speakers , each speakingg(More)
A multi-microphone time-frequency speech masking technique is proposed. This technique utilizes both the time-frequency magnitude and phase information in order to estimate the Signal-to-Noise Ratio (SNR) maximizing masking coefficients for each time-frequency block given that the direction (or alternatively, the time-delay of arrival) of the speaker of(More)
In hands-free voice applications (including voice communication and voice recognition), the captured signal is severely degraded by reverberation when a talker is further away from the microphone. Reverberation significantly degrades speech quality and speech recognition accuracy. As a result, it is necessary to suppress reverberation. Spectral subtraction(More)
Acoustic echo cancellation (AEC) and de-reverberation technologies are increasingly important to improve the voice communication and control performance in challenging acoustic environments. In both voice over IP teleconferencing and voice command control, AEC is needed to remove the far-end speech or the playback audio from the speakers and allow the(More)
In this project, we investigate the degree of interoperability among various fingerprint-matching algorithms using compressed enrollment (template) images compatible with ISO/IEC FCD 19794-3 [1]. The interoperability testing consists of three different fingerprint-matching algorithms: a pattern-based matching algorithm from Bioscrypt, and two minutiae-based(More)
  • 1