{'fraction_non_alphanumeric': 0.019715224534501644, 'fraction_numerical': 0.0, 'mean_word_length': 5.347222222222222, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Interactive visualization of human-machine dialogs

Automated spoken dialog systems require systematic procedures for evaluating performance and diagnosing problems. We present an interactive tool that provides graphical views of how callers navigate through such systems, enabling fine-grained analysis for system evaluation and business intelligence. The input is a feed of call-logs. The output is an empirical dialog trajectory analysis represented as stochastic finite state machines, accessible via the web. Complexity is managed by an automatic tokenization procedure that hides fine details until needed. Users can generate selective views of parts of the dialog at high resolution (with access to call data), or zoom out to a summary. The tool provides dialog system developers with all the information they need from a single source, and is in use with directed-dialog and natural-language applications.