ToBI Annotation Environments

ToBI (for Tones and Break Indices) is a SYSTEM for transcribing the intonational patterns and other aspects of the prosody of English utterances. It was devised by a group of speech scientists from various different disciplines (electrical engineering, psychology, linguistics, etc.) who wanted a common standard for transcribing an agreed-upon set of prosodic elements, in order to be able to share prosodically transcribed databases across research sites in the pursuit of diverse research purposes and varied technological goals.

Comparison of the two environments

Below are two different environments for learning/doing ToBI labeling. Both WaveSurfer and Praat are general tools for analyzing, synthesizing, and manipulating speech, and each of them has its pros and cons.

WaveSurfer's user interface is quite natural and intuitive. It takes very little time to get used to it and start working. Though WaveSurfer is well-suited for a task like ToBI labeling, it is rather limited for more general speech-processing tasks.

Praat is currently the standard tool for speech processing. It is better documented (there is even a Yahoo! Group for Praat users, see below), there are many useful script libraries available, and it has an embedded scripting language that facilitates many tasks. On the other hand, both its user interface and its scripting language are non-standard, unintuitive, and often inconsistent.

About the Cardinal Examples

Finally, no matter what environment you use, make sure you download the Cardinal Examples (see below), a small program that shows an example for each ToBI label. It uses WaveSurfer, so you will need to install that program too.


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ToBI Documentation

ToBI on Praat

ToBI on WaveSurfer

Cardinal Examples

The Cardinal Examples contain one example ToBI-labeled wav file for each ToBI label.

Praat - Resources

Home page and primary documentation: Additional resources:

WaveSurfer - Resources

Home page and primary documentation:
contact: agus [at] last updated 06.07.2017