Humans hold the remarkable capacity to attend to a single person’s voice when many people are talking. Nevertheless, individuals with hearing loss may struggle to tune into a single voice in these types of complex acoustic situations. Current hearing aids can remove background noise but are unable to selectively amplify a single person’s voice without first knowing to whom the listener aims to attend. Studies of multitalker speech perception have demonstrated an enhanced representation of attended speech in the neural responses of a listener, giving rise to the prospect of a brain-controlled hearing aid that uses Auditory Attention Decoding (AAD) algorithms to selectively amplify the target of the listener’s attention as decoded from their neural signals. In this dissertation, I describe experiments using non-invasive and invasive electrophysiology that investigate the encoding and decoding of speech representations that inform our understanding of the influence of attention on speech perception and advance our progress toward brain-controlled hearing devices. First, I explore the efficacy of AAD in improving speech intelligibility when switching attention between different talkers with data recorded non-invasively from listeners with hearing loss. I show that AAD can be effective at improving intelligibility for listeners with hearing loss, but current methods for AAD with non-invasive data are unable to detect changes in attention with sufficient accuracy or speed to improve intelligibility generally. Next, I analyze invasive neural recordings to more clearly establish the boundary between the neural encoding of target and non-target speech during multitalker speech perception. In particular, I investigate whether speech perception can be achieved through glimpses, i.e. spectrotemporal regions where a talker has more energy than the background, or if the recovery of masked regions is also necessary. I find that glimpsed speech is encoded for both target and non-target talkers, while masked speech is encoded for only the target talker, with a greater response latency and distinct anatomical organization compared to glimpsed speech. These findings suggest that glimpsed and masked speech utilize separate encoding mechanisms and that attention enables the recovery of masked speech to support higher-order speech perception. Last, I leverage my theory of the neural encoding of glimpsed and masked speech to design a novel framework for AAD. I show that differentially classifying event-related potentials to glimpsed and masked acoustic events is more effective than current models that ignore the dynamic overlap between a talker and the background. In particular, this framework enables more accurate and stable decoding that is quicker at identifying changes in attention and capable of detecting atypical uses of attention, such as divided attention or inattention. Together, this dissertation identifies key problems in the neural decoding of a listener’s attention, expands our understanding of the influence of attention on the neural encoding of speech, and leverages this understanding to design new methods for AAD that move us closer to the development of effective and intuitive brain-controlled hearing assistive devices.

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Auditory rhythms play a central role in human culture and communication, through both speech and music. The ability to track and predict the organization of events in time helps humans optimize attention, perceive emotion, coordinate actions, and understand social affiliations. The importance of these functions has inspired substantial efforts to model rhythm perception. However, despite a wealth of evidence that pitch influences rhythm perception, with higher speech and music perceived as faster, leading theories and models of rhythm perception have yet to incorporate these effects of pitch. This thesis addresses several empirical questions that have stood in the way of integrating pitch into these models. Specifically, 1) whether the perception of higher pitches as faster generalizes across more than two octaves and above 1000 Hz, 2) whether pitch influences synchronized motor tempo, and 3) whether pitch–timing interactions are bidirectional, such that tempo changes also influence perceived pitch. To answer these questions, we present data from ten experiments including subjective tempo ratings, sensorimotor timing, temporal discrimination, and pitch discrimination tasks. Our results suggest the existence of two separate effects of pitch on perceived timing. First, we present evidence in Chapters 2 and 3 for a unidirectional, negative quadratic effect of absolute pitch on perceived tempo. In this effect, both subjective and sensorimotor tempo rise with pitch between 110 and 440 Hz, peak somewhere between 440 and 1760 Hz, and decrease with pitch above that peak. In Chapters 4 and 5, we present evidence for a bidirectional and approximately linear bias to perceive higher pitches as faster and earlier sounds as higher. We propose that the former effect is most likely innate and a product of the structure of the auditory system, whereas the latter is learned from world structure and originates from cue integration at a later stage of processing. / Dissertation / Doctor of Philosophy (PhD) / Our ability to understand rhythms and find “the beat” in music and speech is key to how we interact with the world and with one another. Rhythm and music are important in every known culture, and synchronizing to rhythms helps us form connections, coordinate, and communicate with others. This thesis explores how another aspect of music—pitch—changes how we hear the beat. Past research suggests music sounds faster to us when played at a higher pitch. Through our work, we discovered that the reverse is also true—musical pitch starts to sound higher as the rhythm speeds up. We also show that pitch changes how fast we move while trying to keep the beat. Studying these pitch and rhythm illusions helps us to better understand how our brains combine information about the melody and rhythm of music, and may help us to develop better medical alarms in the future.