Fast Track: fast (nearly) automatic formant-tracking using Praat

Fast Track is a formant tracker implemented in Praat that attempts to automatically select the best analysis from a set of candidates. The best track is selected by modeling smooth formant contours across the entirety of the sound, providing the researcher with rich information about static and dynamic formant properties. Fast Track returns text files containing acoustic information (formant frequencies, formant bandwidths, fundamental frequency, etc.) sampled every 2 ms, generates images showing the winning analysis and comparing alternate analyses, and creates log files detailing analysis information for each file. Fast Track features a modular workflow that allows for analysis steps to be run (and re-run) independently as necessary, and is designed to allow for easy correction of tracking errors by allowing the user to override the automatic analysis, or manually edit tracks where necessary. In addition, Fast Track includes tools to aggregate data across tokens, and to easily create vowel plots of mean values or time-varying formant contours. The design and use of Fast Track are outlined using a re-analysis of the Hillenbrand et al. (1995) dataset, which suggests that Fast Track can be very accurate in cases where signal properties allow for reliable formant estimates.

Prosodic Analysis and Enhancement of Dysarthric Speech

Dysarthria is a disorder that is caused in the nervous system. It is caused by damage in some parts of the brain such as cerebellum. Because of the damage in brain it causes weakness in muscles used for speech therefore it happens as in mumbled, slurred or slow speech that human and the machine find it difficult to understand such slurred speech. The Automatic Speech Recognizers which were designed for speech intelligibility perform poorly on dysarthric speech recognition. This paper focuses on the transformation of voice for dysarthria to enhance its intelligibility Formant tracking, pitch and energy estimation with durational cues from dysarthric speech facilitate the modification of these trajectories to more closely approximate the desired intelligible target speech. The transformation of the speech is done by using formant re-synthesis, pitch change and duration morphing. The results of such transformation results indicate that the transformation of the pitch and duration step enhances the intelligibility of dysarthric speech and make it easy to understand for humans and machines.