72.4CLApr 22
Aligning Stuttered-Speech Research with End-User Needs: Scoping Review, Survey, and GuidelinesHawau Olamide Toyin, Mutiah Apampa, Toluwani Aremu et al.
Atypical speech is receiving greater attention in speech technology research, but much of this work unfolds with limited interdisciplinary dialogue. For stuttered speech in particular, it is widely recognised that current speech recognition systems fall short in practice, and current evaluation methods and research priorities are not systematically grounded in end-user experiences and needs. In this work, we analyse these gaps through 1) a scoping review of papers that deal with stuttered speech and 2) a survey of 70 stakeholders, including adults who stutter and speech-language pathologists. By analysing these two perspectives, we propose a taxonomy of stuttered-speech research, identify where current research directions diverge from the needs articulated by stakeholders, and conclude by outlining concrete guidelines and directions towards addressing the real needs of the stuttering community.
CLMay 31, 2025
Clinical Annotations for Automatic Stuttering Severity AssessmentAna Rita Valente, Rufael Marew, Hawau Olamide Toyin et al.
Stuttering is a complex disorder that requires specialized expertise for effective assessment and treatment. This paper presents an effort to enhance the FluencyBank dataset with a new stuttering annotation scheme based on established clinical standards. To achieve high-quality annotations, we hired expert clinicians to label the data, ensuring that the resulting annotations mirror real-world clinical expertise. The annotations are multi-modal, incorporating audiovisual features for the detection and classification of stuttering moments, secondary behaviors, and tension scores. In addition to individual annotations, we additionally provide a test set with highly reliable annotations based on expert consensus for assessing individual annotators and machine learning models. Our experiments and analysis illustrate the complexity of this task that necessitates extensive clinical expertise for valid training and evaluation of stuttering assessment models.