Validation of the Adaptive Danish Sentence Test (DAST): A Template-Based Approach for Developing Linguistically Rich Sentence-in-Noise Tests

Background/Objectives: This study describes the development and validation of the Danish Sentence Test (DAST), a Danish-language, adaptive speech-in-noise test constructed from a linguistically balanced corpus using a template-based method. This approach enables controlled linguistic variation while maintaining lexical consistency and may serve as a model for developing similar speech materials in other languages. Methods: Sentences spoken by one female talker from the DAST corpus were sorted into 44 balanced lists of 20 sentences using a psychometric optimization procedure. Speech reception thresholds (SRTs) were measured in 20 normal-hearing participants using headphone playback with speech-shaped noise. Results: The mean SRT across lists was −5.3 dB SNR, with list means within ±0.5 dB of the grand average. The average within-subject standard deviation was 0.7 dB, and the grand average psychometric slope was 18.5%/dB. A relatively small training effect was observed, consistent with the use of linguistically varied, low‑predictability material. Conclusions: DAST provides a linguistically rich and psychometrically well-controlled speech-in-noise test with substantially more material than existing Danish corpora. The template-based method and optimization approach may be of broader methodological interest for developing speech materials in other languages. DAST complements existing Danish-language tests and enables more extensive assessments of speech understanding, including studies requiring large numbers of non-repeated sentence lists.