WaveSurfer makes use of text configuration files to allow the user to specify and automatically set up and reuse specific configurations of panes for purposes of speech analysis, recording, labeling, and so forth. WaveSurfer comes with a handful of predefined configurations, and users can easily define and use their own custom configurations.

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The SpeechMark family of products is designed to detect acoustic landmarks in speech recordings. Landmarks are acoustic events that correlate with changes in speech articulation. The SpeechMark family comprises plug-ins that augment the capabilities of existing third-party software, as well as stand-alone libraries and command line utilities.

The landmark detection process begins by analyzing the signal in several broad frequency bands. Because of the different vocal-tract dimensions, the appropriate frequencies for the bands are different for adults and infants; however, the procedure itself does not vary. First, an energy waveform is constructed in each of the bands. Then the rate of rise (or fall) of the energy is computed, and peaks in the rate are detected. These peaks therefore represent times of abrupt spectral change in the bands. simultaneous peaks in several bands identify consonantal landmarks.

In a significant body of work spanning several decades, Stevens and colleagues suggested that the speech signal can be usefully analyzed in terms of landmarks—that is, acoustic events that correlate with changes in speech articulation [1]. Most research using the landmark approach has focused on the lexical content of speech [2][3]. In our work [4][5] , we have found that tools based on landmarks can be useful for investigating non-lexical attributes of speech, such as syllabic complexity or vowel space area over time. In particular, we have found that landmark-based software tools are well suited for analysis of subtle differences in production of the same speech material by the same speaker.

How are Acoustic Landmarks Detected?

The usual SpeechMark® vowel-space plot for adults includes a polygon that marks the boundaries of typical formant-frequency (F1, F2) pairs for normal adult speakers. The boundary drawn depends on whether the sex of the actual speaker has been specified as male, female, or unknown. The polygon is intended solely as a “fiducial” reference (an aid to the eye) much like grid lines. Like grid lines, it does not depend on the plotted data: part of its value is that it remains constant across all plots for adults of a given sex.

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This document describes the process by which the SpeechMark syllabic cluster analysis operates to group previously computed landmarks. The grouping algorithms were developed to deal with English-focused infant speech including babble—that is, speech whose intended lexical content is unknown (if it exists).

Sequences that would be transcribed as an infant attempt at a speech syllabic cluster were identified, and empirical rules for separating these from the speech stream and from each other were developed based on landmark sequences and timing.

It is important to remember that the syllabic cluster rules so developed are sensitive only to the speech AS UTTERED. They may or may not match syllabic clusters of speech as analyzed by transcription.

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