Treatment of post-stroke apraxia of speech (AOS) requires frequent and ongoing practice with a speech-language pathologist to facilitate lasting behavioral change, which is costly and, therefore, inaccessible to many patients. Thus, there is a critical need to identify novel, cost-effective ways to supplement speech therapy to increase opportunities for practice and optimize treatment outcomes. Our long-term goal is to develop an effective, home-practice, computer-based, motor imagery protocol Motor Imagery for Treatment Enhancement and Efficacy (MI-TEE) which will serve as an adjunct to routine speech therapy to optimize treatment response in persons with AOS. The overall objectives of this application are to (i) evaluate the acceptability and feasibility of MI-TEE as a home practice program and (ii) determine the efficacy of MI-TEE with speech therapy, compared to speech therapy alone, in improving speech production in people with AOS. Our central hypothesis is that MI-TEE will be an accessible, feasible, and efficacious adjunct to speech therapy. To attain our objectives, the following specific aims will be pursued using two single-subject experimental designs with multiple baselines across participants (n=18): 1) Evaluate the acceptability and feasibility of MI-TEE as an adjunct to speech therapy for the rehabilitation of AOS; and 2) Compare the efficacy of adjunctive MI-TEE plus standard speech therapy to standard speech therapy alone. Under the first aim, observational data, surveys, and semi-structured interviews will be employed to assess the acceptability (perceived satisfaction, appropriateness, and intent to continue use) and feasibility (recruitment, retention, and intervention adherence rates) of MI-TEE. For the second aim, accuracy of articulation for trained words and untrained words (generalization) will be measured pre-treatment, repeatedly during the treatment phase, and post-treatment. Improvements in speech accuracy will be documented using a binary scoring system (correct/incorrect). Multilevel analyses will be used to address rate of acquisition, overall change, and response variation across participants.