Understanding speech in noisy settings is one of the biggest challenges for individuals with hearing loss. Traditional speech-in-noise tests play a crucial role in screening for and diagnosing hearing loss, but are resource-intensive to develop, limiting accessibility, particularly in low and middle-income countries. This four-part study introduces an innovative approach using artificial intelligence (AI) to automate the development of such tests. By leveraging text-to-speech (TTS) and automatic speech recognition (ASR) technologies, this approach significantly reduces the cost, time, and resources required for high-quality speech-in-noise testing accessible worldwide. The procedure, named “Aladdin” (Automatic LAnguage-independent Development of the Digits-In-Noise test), creates digits-in-noise (DIN) hearing tests through synthetic speech material and ASR-based level corrections to perceptually equalize the digits, demonstrating characteristics comparable to traditional tests. Notably, Aladdin provides a universal guideline for developing DIN tests across languages, addressing the challenge of comparing test results across variants. This approach, with its potential for broad application in audiology, represents a significant advancement in test development and offers a cost-effective and efficient enhancement to global screening and treatment for hearing loss.

The authors have declared no competing interest.

Health Holland funded this study

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The Vrije universiteit medisch centrum (VUmc) medical research ethics committee determined that the study did not require additional ethics evaluation

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

The data that support the findings of this study are available from the corresponding author upon reasonable request