Comparing the AzBio Sentence-in-Noise Test in English and Spanish in Bilingual Adults.

Abstract

Background: The AzBio Sentence-in-Noise Test was developed in 2011 and was successful in minimizing speech-recognition ceiling effects, giving clinicians and researchers a more accurate representation of a listener's speech-in-noise recognition. Recently, the Spanish version of the AzBio corpus was developed as a sentence-recognition test that could similarly be used to reduce speech-recognition ceiling effects in Spanish-speaking patients. The developers of the AzBio in Spanish included researchers and clinicians from the United States and Colombia. Purpose: The aim of this study was to determine whether the AzBio test batteries in English and Spanish are comparable in difficulty to proficient Spanish-English bilingual adults residing in the United States. Research Design: The study was designed as a standard group comparison. Study Sample: Participants included 20 Spanish-English bilinguals between the ages of 18 and 30 years with hearing thresholds no greater than 25 dB HL in both ears. Data Collection and Analysis: Participants listened to three lists of 20 sentences from the AzBio Sentence-in-Noise Tests in English and in Spanish over two test sessions. Sentences were presented at a +5 dB signal-to-noise ratio in 10-talker babble. Sentence-recognition scores were calculated from total words repeated correctly out of total words presented for all three lists (60 sentences in total) in each language condition. A language experience survey was used to quantify and explore language experience in different dialects of Spanish. Results: Our results indicate that bilingual listeners scored similarly on the English and Spanish test corpora on the group level. On an individual level, participants who spoke a Colombian Spanish dialect were among the highest-performing listeners for the Spanish test corpus and among the lowest-performing listeners for the English corpus. Conclusions: The AzBio in Spanish is a highly valuable clinical tool for evaluating speech recognition in Spanish-speaking patients. Our results suggest that listeners who spoke a Colombian Spanish dialect, consistent with the location where the AzBio in Spanish test was developed, tend to perform better on the Spanish version of the test compared to the English version of the test. Thus, dialectical factors may affect sentence-recognition scores on the AzBio in Spanish corpus. Clinicians in the United States must consider dialect when administering this test corpus because the most common dialect in the United States is Mexican Spanish. Future research should evaluate the education level of listeners to determine the impact of language-specific vocabulary on sentence-recognition performance on both AzBio language corpora.