Speech Identification and Comprehension in the Urban Soundscape

Urban environments are characterised by the presence of copious and unstructured noise. This noise continuously challenges speech intelligibility both in normal-hearing and hearing-impaired individuals. In this paper, we investigate the impact of urban noise, such as traffic, on speech identification and, more generally, speech understanding. With this purpose, we perform listening experiments to evaluate the ability of individuals with normal hearing to detect words and interpret conversational speech in the presence of urban noise (e.g., street drilling, traffic jams). Our experiments confirm previous findings in different acoustic environments and demonstrate that speech identification is influenced by the similarity between the target speech and the masking noise also in urban scenarios. More specifically, we propose the use of the structural similarity index to quantify this similarity. Our analysis confirms that speech identification is more successful in presence of noise with tempo-spectral characteristics different from speech. Moreover, our results show that speech comprehension is not as challenging as word identification in urban sound environments that are characterised by the presence of severe noise. Indeed, our experiments demonstrate that speech comprehension can be fairly successful even in acoustic scenes where the ability to identify speech is highly reduced.