Retest stability and retest reliability were assessed for the Words-in-Noise Test (WIN) in two experiments involving older listeners with sensorineural hearing loss. In Experiment 1, the 70-item WIN protocol was administered during two sessions 12 months apart to examine retest stability on a sample of 315 veterans from four VA Medical Centers. The mean 50% points on the WIN were 12.5- and 12.8-dB S/N for the two sessions with a critical difference of 3.5 dB and an intra-class correlation coefficient of 0.88. [Normal recognition performance on the WIN (50% point) is ≤6-dB S/N.] In Experiment 2, intra- and inter-session retest reliability was examined for the two 35-word WIN protocols on 96 veterans, 48 of whom had mild-to-severe hearing loss (Group 1) and 48 of whom had a moderate-to-severe hearing loss (Group 2). The mean 50% points on the WIN during the two sessions (separated by 40 days) were 13.0- and 13.4-dB S/N (Group 1) and 15.3- and 15.8-dB S/N (Group 2) with no significant intra-session differences. A 3.1-dB critical difference was calculated for the groups combined with intraclass correlations of 0.89 and 0.91 for Group 1 and Group 2, respectively.

The Words-in-Noise (WIN) test uses monosyllabic words in seven signal-to-noise ratios of multitalker babble (MTB) to evaluate the ability of individuals to understand speech in background noise. The purpose of this study was to evaluate the criterion validity of the WIN by comparing recognition performances under MTB and speech-spectrum noise (SSN) using listeners with normal hearing and listeners with hearing loss. The MTB and SSN had identical rms and similar spectra but different amplitude-modulation characteristics. The performances by the listeners with normal hearing, which were 2 dB better in MTB than in SSN, were about 10 dB better than the performances by the listeners with hearing loss, which were about 0.5 dB better in MTB with 56% of the listeners better in MTB and 40% better in SSN. The slopes of the functions for the normal-hearing listeners (8-9%/dB) were steeper than the functions for the listeners with hearing loss (5-6%/dB). The data indicate that the WIN has good criterion validity.

In an initial experiment (Wilson and Weakley, 2004), word recognition was assessed with six digit triplets presented at 14 signal-to-babble ratios (S/B) in 2 dB steps. An abbreviated version of the protocol was developed for clinic use involving three digit triplets at 7 S/Bs in 4 dB steps. The purpose of this experiment was to examine the relationship between the two digit protocols with comparisons made with other variables including age, pure-tone thresholds, subjective measures of understanding speech in quiet and in noise, and word recognition of monosyllabic words in quiet and in babble. Ninety-six listeners with sensorineural hearing loss participated. For equivalent performance, the short version of the digit triplets required (1) a 2.6 dB more favorable S/B than the long version and (2) a 15.1 dB less favorable S/B than the words. Age, hearing loss, and subjective evaluation of the ability to understand speech in quiet and in noise were not related to performance on digits or words in multitalker babble.

The purpose of this study was to determine if performances on a 500 Hz MLD task and a word-recognition task in multitalker babble covaried or varied independently for listeners with normal hearing and for listeners with hearing loss. Young listeners with normal hearing (n = 25) and older listeners (25 per decade from 40-80 years, n = 125) with sensorineural hearing loss were studied. Thresholds at 500 and 1000 Hz were ≤30 dB HL and ≤40 dB HL, respectively, with thresholds above 1000 Hz <100 dB HL. There was no systematic relationship between the 500 Hz MLD and word-recognition performance in multitalker babble. Higher SoNo and SπNo thresholds were observed for the older listeners, but the MLDs were the same for all groups. Word recognition in babble in terms of signal-to-babble ratio was on average 6.5 (40- to 49-year-old group) to 10.8 dB (80- to 89-year-old group) poorer for the older listeners with hearing loss. Neither pure-tone thresholds nor word-recognition abilities in quiet accurately predicted word-recognition performance in multitalker babble.

The purpose of this experiment was to determine the relationship between psychometric functions for words presented in multitalker babble using a descending presentation level protocol and a random presentation level protocol. Forty veterans (mean = 63.5 years) with mild-to-moderate sensorineural hearing losses were enrolled. Seventy of the Northwestern University Auditory Test No. 6 words spoken by the VA female speaker were presented at seven signal-to-babble ratios from 24 to 0 dB (10 words/step). Although the random procedure required 69 sec longer to administer than the descending protocol, there was no significant difference between the results obtained with the two psychophysical methods. There was almost no relation between the perceived ability of the listeners to understand speech in background noise and their measured ability to understand speech in multitalker babble. Likewise, there was a tenuous relation between pure-tone thresholds and performance on the words in babble and between recognition performance in quiet and performance on the words in babble.

Nowadays, everyone is very busy and running around trying to maintain a balance between their work life and family, as the working hours are increasing day by day. In such hassled life people either ignore or do not give enough attention to a healthy diet. An imperative part of a healthy eating routine is the cognizance and maintenance of nourishing data and comprehension of how extraordinary sustenance and nutritious constituents influence our bodies. Besides in the USA, in many other countries, nutritional information is fundamentally passed on to consumers through nutrition labels (NLs) which can be found in all packaged food products in the form of nutrition table. However, sometimes it turns out to be challenging to utilize this information available in these NLs notwithstanding for consumers who are health conscious as they may not be familiar with nutritional terms and discover it hard to relate nutritional information into their day by day activities because of lack of time, inspiration, or training. So it is essential to automate this information gathering and interpretation procedure by incorporating Machine Learning based algorithm to abstract nutritional information from NLs on the grounds that it enhances the consumer’s capacity to participate in nonstop nutritional information gathering and analysis.

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