AutoFocus360 사운드 품질 선호도 및 주장 연구 (AF360)

실험적: 참가자 그룹

참가자는 AutoFocus360과 고정 지향성 마이크를 사용하여 전면, 좌측, 후면, 우측에서 발생하는 두 가지 유형의 잡음 속에서 화자의 대화 장면을 청취하게 됩니다. 조건 순서는 참가자 간 무작위로 배정되며 참가자와 실험자 모두에게 가려집니다.

장치: 오토포커스 360

AutoFocus 360은 보청기 착용자에 대한 음성 발생 방향을 감지하고 음성 방향으로 빔포밍을 조향함으로써 음성 명료도를 향상시키는 기능입니다.

장치: 고정형 지향성 마이크

고정형 지향성 마이크로폰이 보청기 착용자의 정면을 향해 정적 빔포밍을 제공합니다.

Noise Disturbance Sound Quality Attribute

Participants will complete an A-B paired-comparison listening task to assess subjective preference for noise disturbance between two hearing aid conditions. In other words, participants will be asked "which sample has less disturbing noise". During testing, participants will listen to short audio recordings that vary in talker location and noise type. For each trial, participants will indicate which of the two recordings (A or B) has less bothersome background noise. The outcome measure will be the the percentage of "A preferred" versus "B preferred" responses aggregated across all trials and participants for a given noise and talker location. In other words, for a single noise x talker location combination, the outcome measures for AF360 and FWD should add up to 100. Binary preference data will be analyzed using inferential statistics.

Speech Clarity Sound Quality Attribute

Participants will complete an A-B paired-comparison listening task to assess subjective preference for speech clarity between two hearing aid conditions. In other words, participants will be asked "which sample has clearer speech". During testing, participants will listen to short audio recordings that vary in talker location and noise type. For each trial, participants will indicate which of the two recordings (A or B) has clearer speech. The outcome measure will be the proportion of "A preferred" versus "B preferred" responses aggregated across all trials and participants for a given noise and talker location. In other words, for a single noise x talker location combination, the outcome measures for AF360 and FWD should add up to 100. . Binary preference data will be analyzed using inferential statistics.