Stuttering is a communication disorder characterized by disfluencies that are frequent and disruptive to communication. Clinicians extensively use disfluency counts to decide whether a client should be treated, to assess treatment progress, and to document treatment outcomes. Clinicians often do disfluency counts in real-time as a speaker is talking. However, these are not very specific, and cannot be re-examined. Clinicians can also use a verbatim transcription approach, in which they first transcribe exactly what was said, and then mark up the transcript with disfluency codes. This method allows more detailed and accurate counts to be obtained. The long term objective of this project is to build a computer tool that will assist clinicians in performing disfluency counts, both real-time and transcript based. The tool will allow both richer use of these counts, and, in the case of transcript-based counts, much less effort to create the counts. In fact, the amount of time should be reduced enough to enable transcript-based counts to be used in clinical practice. The goal of this Phase I-STTR is to demonstrate the feasibility of a computer tool to assist users in performing both real-time and transcript- based disfluency counts. For real-time counts, we will show that the tool achieves the same reliability and user acceptance as the pencil-and-paper method. We will also investigate whether the real-time counts can be re- examined and corrected (unlike the pencil-and-paper counts). For the transcript-based counts, we will show that the tool, for at least read-speech samples, allows the counts to be done substantially faster and with better reliability than current approaches. This will be achieved by incorporating an Automatic Speech Recognizer (ASR) that will use the story text to assist in transcribing the speech;and by incorporating a powerful user interface that allows the clinician to easily review and correct the automatic transcription. In Phase II, we will demonstrate the increased utility of disfluency counts due to them being stored in a computer file and time-aligned to the audio signal. We will extend the tool so that it can compare disfluency counts across multiple audio files. This will help clinicians better see the impact of their treatment over a period of time on the client's disfluency patterns. We will also demonstrate that the tool can assist clinicians with transcript- based counts of spontaneous speech. Again, we will incorporate an ASR to assist in the transcription process, and we will show that the tool allows transcript-based counts to be performed in substantially less time than current approaches. Furthermore, we will have a several clinicians use the tool over a period of several months with clients. This will demonstrate both the usefulness and practicality of the overall tool, and allow us to determine how to improve and augment it to best suit clinical needs.
Stuttering is a communication disorder characterized by disfluencies that are frequent and disruptive to communication. Clinicians extensively use disfluency counts to decide whether a client should be treated, to assess treatment progress, and to document treatment outcomes. This proposed project will create and evaluate a tool to assist clinicians in producing these counts, and enable more detailed and reliable counts to be employed in clinical practice.
