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

Increasing amounts of public, corporate, and private audio data are available for use, but limited in usefulness by the lack of tools to permit their browsing and search. In this paper, we describe SCANMail, a system that employs automatic speech recognition, information retrieval, information extraction, and human computer interaction technology to permit users to browse and search their voicemail messages by content through a graphical user interface interface. The SCANMail client also provides note-taking capabilities as well as browsing and querying features. A CallerId server also proposes caller names from existing caller acoustic models and is trained from user feedback. An Email server sends the original message plus its transcription to a mailing address specified in the user's profile. 1.

SCANMail is a prototype system developed at AT&T Labs for the purpose of providing useful tools for managing and searching through voicemail messages. Content is extracted from voicemail messages using various speech and text processing tools. One such content category is the identity of the message caller. This paper describes CallerID, the server tool attached to SCANMail for the purpose of providing caller labels for voicemail messages. CallerID make use of text independent speaker recognition techniques. Two kinds of requests are handled by the CallerID server. A request triggered by the arrival of a new voicemail message results in the processing of the message to score it against the models of callers assigned to the user (recipient) in order to propose the identity of the caller. A second request is initiated by a user who provides a caller label for a message he/she has reviewed. CallerID processes the message and uses it to train or adapt a speaker model for the caller whose label is provided. The paper describes in detail the CallerID functions and provides some results of performance evaluations of the caller identification capability.

Article Recommending and evaluating choices in a virtual community of use Share on Authors: Will Hill Bellcore, 445 South Street, Morristown, NJ Bellcore, 445 South Street, Morristown, NJView Profile , Larry Stead Bellcore, 445 South Street, Morristown, NJ Bellcore, 445 South Street, Morristown, NJView Profile , Mark Rosenstein Bellcore, 445 South Street, Morristown, NJ Bellcore, 445 South Street, Morristown, NJView Profile , George Furnas Bellcore, 445 South Street, Morristown, NJ Bellcore, 445 South Street, Morristown, NJView Profile Authors Info & Claims CHI '95: Proceedings of the SIGCHI Conference on Human Factors in Computing SystemsMay 1995 Pages 194–201https://doi.org/10.1145/223904.223929Online:01 May 1995Publication History 590citation5,263DownloadsMetricsTotal Citations590Total Downloads5,263Last 12 Months235Last 6 weeks30 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access