“…We conducted a randomized control trial comparing two intensive treatments, voice (LSVT LOUD) or articulation (LSVT ARTIC) to assess single word intelligibility in the presence of background noise (babble and mall). Participants (64 PD and 20 Healthy) read words from the diagnostic rhyme test (DRT), an ANSI Standard for measuring intelligibility of speech, before and after one month (treatment or no treatment). …”
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“…Participants completed a picture description task via videoconferencing software while both the speaker (the participant) and listener (the experimenter) were exposed to multi-talker babble. Speakers produced fewer T-units, clauses, and words as well as fewer, but longer, unfilled pauses in noise. …”
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“…Auditory processing elements evaluated were speech recognition in babble, rhythmic advantage in speech recognition, short-term working memory, temporal resolution, and frequency discrimination threshold detection. …”
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“…Speech reception thresholds (SRTs) were adaptively measured for simple sentences in speech babble. Melodic contour identification (MCI) was measured with and without a masker instrument; the fundamental frequency of the masker was varied to be overlapping or non-overlapping with the target contour. …”
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“…The types and patterns of errors made on the backward digit span in quiet and multitalker babble at -5 dB signal-to-noise ratio (SNR) were analyzed. …”
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“…However, air-conduced speech is hard to differentiate from babble or white noise signals. OBJECTIVE: To overcome this problem, the proposed algorithm uses the bone-conduction speech signals and soft thresholding based on the Shannon entropy principle and cross-correlation of air- and bone-conduction signals. …”
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“…This study investigated the energetic and informational masking components of multi‐talker babble noise and their influence on neural tracking of the speech envelope in a sample of healthy older adults. …”
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“…In Experiment 1, 45 NH young adults listened to two lists accompanied by four-talker babble noise (4TBN). Experiment 2 presented the sentences amidst 4TBN or speech-shaped noise (SSN) to 80 participants in four age groups. …”
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“…Steady (pink noise) and non-steady noise (cafeteria babble noise) were used to simulate noisy environments. …”
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“…For the first time, we investigated whether auditory (three-talker babble) and visual (short idioms appearing next to a target sentence on the screen) noise would trigger greater reliance on semantics and make readers of Russian sentences process the sentences superficially. …”
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“…METHOD: A support vector machine (SVM) algorithm was used to classify the fricatives extracted from the TIMIT database in quiet and also in speech babble noise at various signal-to-noise ratios (SNRs). …”
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“…Method: Identification of 12 English vowels was measured in quiet and in long-term speech-shaped noise and multi-talker babble (MTB) noise for English- (EN), Chinese- (CN) and Korean-native (KN) listeners at various signal-to-noise ratios (SNRs). …”
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“…The maskers consisted of stationary and fluctuating noise and two-talker babble in Swedish and English. Twenty-three hearing-impaired native Swedish listeners participated, aged between 28 and 65 years. …”
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“…We perform real-time inferencing of our CNN model on the prototyped platform with low latency (21 milliseconds (ms) per frame with a frame length of 30 ms) and high accuracy (i.e. 89.68% under Babble noise condition at 5dB SNR). Lastly, we provide a detailed explanation of real-time implementation and on-device performance (including peak power consumption metrics) that sets this work apart from previously published works. …”
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“…Participants were presented with spoken sentences in babble noise either in auditory-only or auditory-visual conditions with various SNRs at −7, −5, −3, −1, and 1 dB. …”
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“…Young adults with normal hearing listened to sentences masked by multitalker babble in which sentence-final words were either predictable or unpredictable. …”
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“…A text-to-speech synthesis engine was used to synthesize Cantonese daily-use sentences with each word carrying an original or a flat lexical tone, which were then presented to 97 participants in quiet, in speech-shaped noise (SSN), and in two-talker babble (TTB) noise conditions. Both target sentences and noises were presented at 65 dB binaurally via insert headphones. …”
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“…Here, we combined electroencephalography while simultaneously measuring intelligibility of spoken sentences amidst two different interfering sounds: multi-talker babble or speech-shaped noise. We find that induced parieto-occipital alpha (7–15 Hz; thought to modulate attentional focus) and frontal beta (13–30 Hz; associated with maintenance of the current sensorimotor state and predictive coding) oscillations covary with trial-wise percent-correct scores; importantly, alpha and beta power provide significant independent contributions to predicting single-trial behavioral outcomes. …”
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“…Clinical comparisons between programs were conducted across the following listening environments; quiet, speech weighted noise (co-located and spatially separated noise), and 4-talker babble (co-located and spatially separated noise). …”
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“…In a manner that mirrors motor babble, the network can also teach itself to learn through trial and error. …”
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