Sound masking by a low-pitch speech-shaped noise improves a social robot's talk in noisy environments

Introduction: There has been a surge in the use of social robots for providing information, persuasion, and entertainment in noisy public spaces in recent years. Considering the well-documented negative effect of noise on human cognition, masking sounds have been introduced. Masking sounds work, in principle, by making the intrusive background speeches less intelligible, and hence, less distracting. However, this reduced distraction comes with the cost of increasing annoyance and reduced cognitive performance in the users of masking sounds. Methods: In a previous study, it was shown that reducing the fundamental frequency of the speech-shaped noise as a masking sound significantly contributes to its being less annoying and more efficient. In this study, the effectiveness of the proposed masking sound was tested on the performance of subjects listening to a lecture given by a social robot in a noisy cocktail party environment. Results: The results indicate that the presence of the masking sound significantly increased speech comprehension, perceived understandability, acoustic satisfaction, and sound privacy of the individuals listening to the robot in an adverse listening condition. Discussion: To the knowledge of the authors, no previous work has investigated the application of sound masking technology in human-robot interaction designs. The future directions of this trend are discussed.

Towards a simultaneously speaking bilingual robot: Primary study on the effect of gender and pitch of the robot's voice

With fast and reliable international transportation, more people with different language backgrounds can interact now. As a result, the need for communicative agents fluent in several languages to assist those people is highlighted. The high cost of hiring human attendants fluent in several languages makes using social robots a more affordable alternative in international gatherings. A social robot capable of presenting a piece of information in more than one language at the same time to its audience is the goal of this line of study. However, the negative effect of background noise on speech comprehension in humans is well-established. Hence, presenting a piece of information in two different languages at the same time by the robot creates an adverse listening condition for both individuals listening to the speech of such a bilingual robot. In this study, we investigated whether manipulating the pitch and gender of the robot's voice could affect human subjects' memory of the presented information in the presence of background noise. The results indicate that the pitch and gender of the speaking voice do indeed affect our memory of the presented information. when a male voice was used, a higher pitch resulted in significantly better memory performance than a lower pitch. Contrarily, when a female voice was used, a lower pitch resulted in significantly better memory in participants than a higher pitch. Both male and female subjects performed significantly better with a female voice in a noisy background. In nutshell, the result of this study suggests using a female voice for robots in noisy conditions, as in the case of simultaneously speaking robots, can significantly improve the retrieval of presented information in human subjects.

Expansion in speech time can restore comprehension in a simultaneously speaking bilingual robot

Introduction: In this study, the development of a social robot, capable of giving speech simultaneously in more than one language was in mind. However, the negative effect of background noise on speech comprehension is well-documented in previous works. This deteriorating effect is more highlighted when the background noise has speech-like properties. Hence, the presence of speech as the background noise in a simultaneously speaking bilingual robot can be fatal for the speech comprehension of each person listening to the robot. Methods: To improve speech comprehension and consequently, user experience in the intended bilingual robot, the effect of time expansion on speech comprehension in a multi-talker speech scenario was investigated. Sentence recognition, speech comprehension, and subjective evaluation tasks were implemented in the study. Results: The obtained results suggest that a reduced speech rate, leading to an expansion in the speech time, in addition to increased pause duration in both the target and background speeches can lead to statistically significant improvement in both sentence recognition, and speech comprehension of participants. More interestingly, participants got a higher score in the time-expanded multi-talker speech than in the standard-speed single-talker speech in the speech comprehension and, in the sentence recognition task. However, this positive effect could not be attributed merely to the time expansion, as we could not repeat the same positive effect in a time-expanded single-talker speech. Discussion: The results obtained in this study suggest a facilitating effect of the presence of the background speech in a simultaneously speaking bilingual robot provided that both languages are presented in a time-expanded manner. The implications of such a simultaneously speaking robot are discussed.