RESUMEN
OBJECTIVE: Automated speech recognition (ASR) systems have become increasingly sophisticated, accurate, and deployable on many digital devices, including on a smartphone. This pilot study aims to examine the speech recognition performance of ASR apps using audiological speech tests. In addition, we compare ASR speech recognition performance to normal hearing and hearing impaired listeners and evaluate if standard clinical audiological tests are a meaningful and quick measure of the performance of ASR apps. METHODS: Four apps have been tested on a smartphone, respectively AVA, Earfy, Live Transcribe, and Speechy. The Dutch audiological speech tests performed were speech audiometry in quiet (Dutch CNC-test), Digits-in-Noise (DIN)-test with steady-state speech-shaped noise, sentences in quiet and in averaged long-term speech-shaped spectrum noise (Plomp-test). For comparison, the app's ability to transcribe a spoken dialogue (Dutch and English) was tested. RESULTS: All apps scored at least 50% phonemes correct on the Dutch CNC-test for a conversational speech intensity level (65 dB SPL) and achieved 90-100% phoneme recognition at higher intensity levels. On the DIN-test, AVA and Live Transcribe had the lowest (best) signal-to-noise ratio +8 dB. The lowest signal-to-noise measured with the Plomp-test was +8 to 9 dB for Earfy (Android) and Live Transcribe (Android). Overall, the word error rate for the dialogue in English (19-34%) was lower (better) than for the Dutch dialogue (25-66%). CONCLUSION: The performance of the apps was limited on audiological tests that provide little linguistic context or use low signal to noise levels. For Dutch audiological speech tests in quiet, ASR apps performed similarly to a person with a moderate hearing loss. In noise, the ASR apps performed more poorly than most profoundly deaf people using a hearing aid or cochlear implant. Adding new performance metrics including the semantic difference as a function of SNR and reverberation time could help to monitor and further improve ASR performance.
RESUMEN
Electronic health record (EHR) was hailed as a major step towards making healthcare more transparent and accountable. All the developed nations digitised their health records which were meant to be safe, secure and could be accessed on demand. This was intended to benefit all stakeholders. However, the jury is still out if the EHR has been worth it. There have been incidences of data breaches despite cybersecurity checks and of manipulation compromising clinicians' integrity and patients' safety. EHRs have also been blamed for doctor burnout in overloading them with a largely avoidable administrative burden. The lack of interoperability amongst various EHR software systems is creating obstacles in seamless workflow. Artificial intelligence is now being used to overcome deficiencies of the EHR. Emerging data from real-world usage of EHR is providing useful inputs which would be helpful in making it a better system. This review critically appraises the current status and issues with the EHR and provides an overview of the key innovations which are being implemented to make the system more efficient for health care providers leading to a reduction in their administrative burden.