Development of a corpus of Mandarin sentences in babble with homogeneity optimized via psychometric evaluation

Xi, Xin; Ching, Teresa Y. C.; Ji, Fei; Zhao, Yang; Li, Jia Nan; Seymour, John P.; Hong, Meng; Chen, Ai Ting; Dillon, Harvey

doi:10.3109/14992027.2011.642011

Cited by 26 publications

(16 citation statements)

References 10 publications

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“…The present mean SRT were somewhat better than those reported for BKB-like Mandarin sentences in noise (−6 dB; Xi et al, 2012) and MHINT sentences in noise (−4.3 dB; Wong et al, 2007), possibly due to differences in test paradigm (closed- versus open-set), speech materials, talkers, etc.…”

Section: Discussioncontrasting

confidence: 88%

“…The recording and editing methods used in previous matrix studies resulted in several hundred sentences at most, while the CMS allows for 100,000 sentences. This was an important consideration for the development of the CMS, as the available Mandarin speech tests (Wong et al, 2007; Fu et al, 2011; Xi et al, 2012) offer too few sentences for repeated testing as is often required for research. While the methods used in previous matrix tests may allow for more natural-sounding sentences, it is unclear how this might affect intelligibility in these tests.…”

Section: Discussionmentioning

confidence: 99%

“…Relatively few speech materials been developed with which to evaluate intelligibility (Wong et al, 2007, Fu et al, 2011; Xi et al, 2012), and the speech materials are limited to a few hundred sentences, making it difficult to repeatedly measure performance within subjects. As such, a matrix-like Chinese sentence test, given its potential to generate 100,000 unique sentences, would benefit both clinical and research practice.…”

Section: Introductionmentioning

confidence: 99%

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The development and validation of the Closed-set Mandarin Sentence (CMS) test

Tao

Galvin

et al. 2017

Speech Communication

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Matrix-styled sentence tests offer a closed-set paradigm that may be useful when evaluating speech intelligibility. Ideally, sentence test materials should reflect the distribution of phonemes within the target language. We developed and validated the Closed-set Mandarin Sentence (CMS) test to assess Mandarin speech intelligibility in noise. CMS test materials were selected to be familiar words and to represent the natural distribution of vowels, consonants, and lexical tones found in Mandarin Chinese. Ten key words in each of five categories (Name, Verb, Number, Color, and Fruit) were produced by a native Mandarin talker, resulting in a total of 50 words that could be combined to produce 100,000 unique sentences. Normative data were collected in 10 normal-hearing, adult Mandarin-speaking Chinese listeners using a closed-set test paradigm. Two test runs were conducted for each subject, and 20 sentences per run were randomly generated while ensuring that each word was presented only twice in each run. First, the level of the words in each category were adjusted to produce equal intelligibility in noise. Test-retest reliability for word-in-sentence recognition was excellent according to Cronbach’s alpha (0.952). After the category level adjustments, speech reception thresholds (SRTs) for sentences in noise, defined as the signal-to-noise ratio (SNR) that produced 50% correct whole sentence recognition, were adaptively measured by adjusting the SNR according to the correctness of response. The mean SRT was −7.9 (SE=0.41) and −8.1 (SE=0.34) dB for runs 1 and 2, respectively. The mean standard deviation across runs was 0.93 dB, and paired t-tests showed no significant difference between runs 1 and 2 (p=0.74) despite random sentences being generated for each run and each subject. The results suggest that the CMS provides large stimulus set with which to repeatedly and reliably measure Mandarin-speaking listeners’ speech understanding in noise using a closed-set paradigm.

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Section: Discussioncontrasting

confidence: 88%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The development and validation of the Closed-set Mandarin Sentence (CMS) test

Tao

Galvin

et al. 2017

Speech Communication

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“…The three baseline blocks (three algorithms in quiet) were conducted first in a random order, followed by the remaining 18 blocks in a random order. We used sentence materials from two published Mandarin speech databases: the PLA General Hospital sentence recognition test (Xi et al, 2012) corpus and the House Research Institute sentence recognition test (Fu et al, 2011) corpus. The PLA General Hospital corpus consists of 12 lists each with 11 sentences, and each sentence includes six to eight key words.…”

Section: Procedures and Materialsmentioning

confidence: 99%

A New Approach for Noise Suppression in Cochlear Implants: A Single-Channel Noise Reduction Algorithm1

Zhou

Wang²,

Zheng

et al. 2020

Front. Neurosci.

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The cochlea "translates" the in-air vibrational acoustic "language" into the spikes of neural "language" that are then transmitted to the brain for auditory understanding and/or perception. During this intracochlear "translation" process, high resolution in time-frequency-intensity domains guarantees the high quality of the input neural information for the brain, which is vital for our outstanding hearing abilities. However, cochlear implants (CIs) have coarse artificial coding and interfaces, and CI users experience more challenges in common acoustic environments than their normalhearing (NH) peers. Noise from sound sources that a listener has no interest in may be neglected by NH listeners, but they may distract a CI user. We discuss the CI noise-suppression techniques and introduce noise management for a new implant system. The monaural signal-to-noise ratio estimation-based noise suppression algorithm "eVoice," which is incorporated in the processors of Nurotron R Enduro TM , was evaluated in two speech perception experiments. The results show that speech intelligibility in stationary speech-shaped noise can be significantly improved with eVoice. Similar results have been observed in other CI devices with single-channel noise reduction techniques. Specifically, the mean speech reception threshold decrease in the present study was 2.2 dB. The Nurotron society already has more than 10,000 users, and eVoice is a start for noise management in the new system. Future steps on nonstationary-noise suppression, spatial-source separation, bilateral hearing, microphone configuration, and environment specification are warranted. The existing evidence, including our research, suggests that noise-suppression techniques should be applied in CI systems. The artificial hearing of CI listeners requires more advanced signal processing techniques to reduce brain effort and increase intelligibility in noisy settings.

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“…Familiarization with the speech material was provided by administering one list in quiet with the ACE strategy and one practice list in noise with each of the strategies prior to the test run on each test occasion. The corpus of Mandarin sentences was developed by Xi et al (2012) and consisted of multiple lists of 20 sentences. The sentences were mined from utterances spoken by 4-5 year old Chinese children living in Beijing and recorded using a male speaker with an average F0 of approximately 140 Hz.…”

Section: Sentences In Noisementioning

confidence: 99%

Results using the OPAL strategy in Mandarin speaking cochlear implant recipients

Vandali

Dawson

Arora

2016

International Journal of Audiology

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Development of a corpus of Mandarin sentences in babble with homogeneity optimized via psychometric evaluation

Abstract: The experiments established a corpus of Mandarin BKB-like sentences with four-talker babble as competing noise, in which the test items' homogeneity was optimized via psychometric evaluation (HOPE).

Cited by 26 publications

References 10 publications

The development and validation of the Closed-set Mandarin Sentence (CMS) test

The development and validation of the Closed-set Mandarin Sentence (CMS) test

A New Approach for Noise Suppression in Cochlear Implants: A Single-Channel Noise Reduction Algorithm1

Results using the OPAL strategy in Mandarin speaking cochlear implant recipients

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