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This paper evaluates the effectiveness of combining speech modification techniques that enhance transition components with active noise cancellation to improve the intelligibility of speech in noise. Two speech modification techniques were considered. One is based on wavelet-packet analysis, and the second uses a fixed filter, derived from time-frequency analysis, that emphasizes high frequencies. Active noise cancellation was provided by Bose noise-cancelling headphones. The test noise was real, generated by a ground auxiliary generator on the tarmac at an Air National Guard facility. The test signals were speech tokens from the modified rhyme (psycho-acoustic) test, recorded by a male speaker. This paradigm was used to measure word recognition rates at various signal-to-noise ratios. Active noise cancellation by itself provided over 40% increase in word recognition, while the modified speech and fixed filter techniques alone provided up to 20% improvement, depending on the signal-to-noise ratio. In combination, the speech modification approaches provided over 15% additional improvement in intelligibility over noise cancellation alone.

The role of transient speech components on speech intelligibility was investigated. Speech was decomposed into two components--quasi-steady-state (QSS) and transient--using a set of time-varying filters whose center frequencies and bandwidths were controlled to identify the strongest formant components in speech. The relative energy and intelligibility of the QSS and transient components were compared to original speech. Most of the speech energy was in the QSS component, but this component had low intelligibility. The transient component had much lower energy but was almost as intelligible as the original speech, suggesting that the transient component included speech elements important to speech perception. A modified version of speech was produced by amplifying the transient component and recombining it with the original speech. The intelligibility of the modified speech in background noise was compared to that of the original speech, using a psychoacoustic procedure based on the modified rhyme protocol. Word recognition rates for the modified speech were significantly higher at low signal-to-noise ratios (SNRs), with minimal effect on intelligibility at higher SNRs. These results suggest that amplification of transient information may improve the intelligibility of speech in noise and that this improvement is more effective in severe noise conditions.

Consonants are recognized to dominate higher frequencies of the speech spectrum and to carry more information than vowels, but both demonstrate quasi-steady state (QSS) and transient components, such as vowel to consonant transitions. Fixed filters somewhat separate these effects, but probably not optimally, given diverse words, speakers, and situations, and we suggest that important speech information is contained in transient speech components. To study the relative intelligibility of transient versus steady-state components, we employed an algorithm based on time-frequency analysis to extract QSS energy from the speech signal, leaving a residual signal of predominantly transient components. Psychometric functions were measured for speech recognition of processed and unprocessed monosyllabic words. The transient components were found to account for approximately 2% of the energy of the original speech, yet were nearly equally intelligible. As hypothesized, the QSS components contained much greater energy while providing significantly less intelligibility.

The purpose of this study is to create information and signal processing algorithms to enhance the interpretation of speech in noise. An algorithm based on time-frequency analysis was employed to extract quasi-steady-state (QSS) energy from the speech signal, leaving a residual signal of predominantly transient components. The transient component was selectively amplified and recombined with the original speech to generate enhanced speech. The energy of the enhanced speech was adjusted to be equal to that of the original speech, and the intelligibility of the enhanced speech was compared to that of the original speech in background noise. Psychometric functions showed the enhanced speech had higher recognition scores at most noise levels, with greater improvement at lower SNRs. These results suggest that subjects can identify enhanced speech better than the original speech at severe noise conditions

Moving visual scenes with sinusoidal motion have been used to study the role of vision in human balance. We applied a "chirping" visual perturbation (increasing/decreasing frequency of motion), and time-frequency analyzed the resulting center-of-pressure (COP) under the feet in healthy and vestibularly impaired subjects. Differences between healthy and impaired subjects were observed.

Temporomandibular joint (TMJ) sounds and motion were recorded during clinically-derived two movements-simple jaw opening and jaw protrusion followed by opening-from ten patients. A new time-frequency method-radially Gaussian kernel (RGK) distribution-was applied to classify the TMJ clicking sounds into six groups, type I to type VI, based upon time-frequency patterns of energy distribution. The number of clicks and percentage of each type were examined. During the two movements, type I and type IV patterns were most frequently observed and type II and type III were rarely found. Type V and type VI were rarely found during opening movements. However, they were frequently observed during the protrusion phase of the second movement. Relations between the two movements were examined by the prevalence of each type. It was found that some patients tended to have the same types of clicks during the same movements.

Temporomandibular joint (TMJ) sounds and motion were recorded during two clinically-derived movements--simple jaw opening and jaw protrusion followed by opening--from ten patients. A new time-frequency method--radially Gaussian kernel distribution--was applied to classify the TMJ clicking sounds into six groups, type I to type VI, based on the time-frequency patterns of energy distribution. The number of clicks and percentage of each type were examined. Relations between the two movements were examined by the prevalence of each type. A detailed classification of TMJ clicking sounds is provided by time-frequency patterns and may provide a better understanding of temporomandibular disorders.

Consonants are recognized to dominate higher frequencies of the speech spectrum and to carry more information than vowels, but both demonstrate quasi‐steady state and transient components, such as vowel to consonant transitions. Fixed filters somewhat separate these effects, but probably not optimally, given diverse words, speakers, and situations. To enhance the transient characteristics of speech, this study used time‐varying adaptive filters [Rao and Kumaresan, IEEE Trans. Speech Audio Process. 8, 240–254 (2000)], following high‐pass filtering at 700 Hz (well‐known to have minimal effect on intelligibility), to extract predominantly steady‐state components of speech material (CVC words, NU‐6). The transient component was the difference between the sum of the filter outputs and the original signal. Psychometric functions were determined in five subjects with and without background noise and fitted by ogives. The transient components averaged filtered speech energy, but PBmax was not significantly differ...