Engineering topics

Kozel, David

Publications and source records attributed to Kozel, David.

4 records

NASA NTRS2007

Communication system with adaptive noise suppression

A signal-to-noise ratio dependent adaptive spectral subtraction process eliminates noise from noise-corrupted speech signals. The process first pre-emphasizes the frequency components of the input sound signal which contain the consonant information in human speech. Next, a signal-to-noise ratio is determined and a spectral subtraction proportion adjusted appropriately. After spectral subtraction, low amplitude signals can be squelched. A single microphone is used to obtain both the noise-corrupted speech and the average noise estimate. This is done by determining if the frame of data being sampled is a voiced or unvoiced frame. During unvoiced frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Spectral subtraction may be performed on a composite noise-corrupted signal, or upon individual sub-bands of the noise-corrupted signal. Pre-averaging of the input signal's magnitude spectrum over multiple time frames may be performed to reduce musical noise.

Kozel, David↗

NASA NTRS2003

Adaptive Suppression of Noise in Voice Communications

A subsystem for the adaptive suppression of noise in a voice communication system effects a high level of reduction of noise that enters the system through microphones. The subsystem includes a digital signal processor (DSP) plus circuitry that implements voice-recognition and spectral- manipulation techniques. The development of the adaptive noise-suppression subsystem was prompted by the following considerations: During processing of the space shuttle at Kennedy Space Center, voice communications among test team members have been significantly impaired in several instances because some test participants have had to communicate from locations with high ambient noise levels. Ear protection for the personnel involved is commercially available and is used in such situations. However, commercially available noise-canceling microphones do not provide sufficient reduction of noise that enters through microphones and thus becomes transmitted on outbound communication links.

Kozel, David↗

NASA NTRS2000

Noise Reduction using Frequency Sub-Band Adaptive Spectral Subtraction

A frequency sub-band based adaptive spectral subtraction algorithm is developed to remove noise from noise-corrupted speech signals. A single microphone is used to obtain both the noise-corrupted speech and the estimate of the statistics of the noise. The statistics of the noise are estimated during time frames that do not contain speech. These statistics are used to determine if future time frames contain speech. During speech time frames, the algorithm determines which frequency sub-bands contain useful speech information and which frequency sub-bands contain only noise. The frequency sub-bands, which contain only noise, are subtracted off at a larger proportion so the noise does not compete with the speech information. Simulation results are presented.

Kozel, David↗

NASA NTRS1996

Adaptive Noise Suppression Using Digital Signal Processing

A signal to noise ratio dependent adaptive spectral subtraction algorithm is developed to eliminate noise from noise corrupted speech signals. The algorithm determines the signal to noise ratio and adjusts the spectral subtraction proportion appropriately. After spectra subtraction low amplitude signals are squelched. A single microphone is used to obtain both eh noise corrupted speech and the average noise estimate. This is done by determining if the frame of data being sampled is a voiced or unvoiced frame. During unvoice frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Applications include the emergency egress vehicle and the crawler transporter.

Kozel, David↗