Computer-assisted syllable analysis of continuous speech as a measure of child speech disordera).

In this study, a computer-driven, phoneme-agnostic method was explored for assessing speech disorders (SDs) in children, bypassing traditional labor-intensive phonetic transcription. Using the SpeechMark® automatic syllabic cluster (SC) analysis, which detects sequences of acoustic features that characterize well-formed syllables, 1952 American English utterances of 60 preschoolers were analyzed [16 with speech disorder present (SD-P) and 44 with speech disorder not present (SD-NP)] from two dialectal areas. A four-factor regression analysis evaluated the robustness of seven automated measures produced by SpeechMark® and their interactions.

Differences in speech articulatory timing and associations with pragmatic language ability in autism.

Background: Speech articulation difficulties have not traditionally been considered to be a feature of Autism Spectrum Disorder (ASD). In contrast, speech prosodic differences have been widely reported in ASD, and may even be expressed in subtle form among clinically unaffected first-degree relatives, representing the expression of underlying genetic liability. Some evidence has challenged this traditional dichotomy, suggesting that differences in speech articulatory mechanisms may be evident in ASD, and potentially related to perceived prosodic differences.

SpeechMark Acoustic Landmark Tool: Application to Voice Pathology.

One area of voice research that has historically been understudied is the interaction between voice pathology and acoustic aspects of the speech signal that affect intelligibility. Landmark-based software tools are particularly suited to fast, automatic analysis of small, non-lexical differences in the acoustic signal reflecting the production of speech. We are building a tool set that provides fast, automatic summary statistics for measures of speech acoustics based on Stevens' paradigm of landmarks, points in an utterance around which information about articulatory events can be extracted.