Increasing amounts of public, corporate, and private speech data are now available on-line. These are limited in their usefulness, however, by the lack of tools to permit their browsing and search. The goal of our research is to provide tools to overcome the inherent difficulties of speech access, by supporting visual scanning, search, and information extraction. We describe a novel principle for the design of UIs to speech data: What You See Is Almost What You Hear (WYSIAWYH). In WYSIAWYH, automatic speech recognition (ASR) generates a transcript of the speech data. The transcript is then used as a visual analogue to that underlying data. A graphical user interface allows users to visually scan, read, annotate and search these transcripts. Users can also use the transcript to access and play specific regions of the underlying message. We first summarize previous studies of voicemail usage that motivated the WYSIAWYH principle, and describe a voicemail UI, SCANMail, that embodies WYSIAWYH. We report on a laboratory experiment and a two-month field trial evaluation. SCANMail outperformed a state of the art voicemail system on core voicemail tasks. This was attributable to SCANMail’s support for visual scanning, search and information extraction. While the ASR transcripts contain errors, they nevertheless improve the efficiency of voicemail processing. Transcripts either provide enough information for users to extract key points or to navigate to important regions of the underlying speech, which they can then play directly.

stevew/julia/urs @ research.att.com Voicemail is a pervasive, but under-researched tool for workplace communication. Despite potential advantages of voicemail over email, current phone-based voicemail UIs are highly problematic for users. We present a novel, Web-based, voicemail interface, Jotmail. The design was based on data from several studies of voicemail tasks and user strategies. The GUI has two main elements: (a) personal annotations that serve as a visual analogue to underlying speech; (b) automatically derived message header information. We evaluated Jotmail in an 8-week field trial, where people used it as their only means for accessing voicemail. Jotmail was successful in supporting most key voicemail tasks, although users ' electronic annotation and archiving behaviors were different from our initial predictions. Our results argue for the utility of a combination of annotation based indexing and automatically derived information, as a general technique for accessing speech archives.

When users access information from text, they engage in strategic fixation, visually scanning the text to focus on regions of interest. However, because speech is both serial and ephemeral, it does not readily support strategic fixation. This paper describes two design principles, indexing and transcript-centric access that address the problem of speech access by supporting strategic fixation. Indexing involves users constructing external visual indices into speech. Users visually scan these indices to find information-rich regions of speech for more detailed processing and playback. Transcription involves transcribing speech using automatic speech recognition (ASR) and enriching that transcription with visual cues. The resulting enriched transcript is time-aligned to the original speech, allowing users to scan the transcript as a whole or the additional visual cues present in the transcript, to fixate and play regions of interest. We tested the effectiveness of these two approaches on a set of reference tasks derived from observations of current voicemail practice. A field trial evaluation of JotMail, an indexed-based interface similar to commercial unified messaging clients, showed that our approaches were effective in supporting speech scanning, information extraction and status tracking, but not archive management. However, users found it onerous to take manual notes with JotMail to provide effective retrieval indices. We therefore built SCANMail, a transcript-based interface that constructs indices automatically, using ASR to generate a transcript of the speech data. SCANMail also uses information extraction techniques to identify regions of