… speech recognition accuracy has the potential to cause clinical harm [6]. The recent development
of end-to-end speech … experiences in building a speech recognition system with LAS …

… speech recognition accuracy has the potential to cause clinical harm [6]. The recent development
of end-to-end speech … experiences in building a speech recognition system with LAS …

… We are implementing the speech engine in python and using speech recognition libraries.
Our voice recognition medical conversation application is in a first-level code and design …

… to a conversation between a patient and a provider, (b) uses automatic speech recognition
… optimized via customization for the specific context, ie doctor-patient medical conversations. …

… Inclusion criteria were: all papers that referred to speech recognition (SR) in health care
settings, used by health professionals (allied health, medicine, nursing, technical or support staff)…

… Speech recognition is the first step to understand medical conversations. Before delving into
… medical conversations and the associated challenges. The audio in medical conversations …

… speech diarization or speech recognition. As mentioned in Introduction (Section 1), speech
… We also use ASR (automatic speech recognition) interchangeably with speech recognition. …

… Domain adaptation with off-the-shelf ASR has been tried for pure speech recognition tasks
in high and low resource scenarios with various training strategies (Swietojanski and Renals…

… conversational speech recognition for medical conversations … simulated patient-clinician
conversations 24 . They concluded … to medical conversation ASR and patient/clinician speaker …

… Our approach to this problem is to capture medical conversations as an audio recording,
use automatic speech recognition (ASR) to transcribe the conversations, and, then, extract or …