Spoken language resources (SLRs) are essential for both research and application development. In this article we clarify the concept of SLR validation. We define validation and how it differs from evaluation. Further, relevant principles of SLR validation are outlined. We argue that the best way to validate SLRs is to implement validation throughout SLR production and have it carried out by an external and experienced institute. We address which tasks should be carried out by the validation institute, and which not. Further, we list the basic issues that validation criteria for SLR should address. A standard validation protocol is shown, illustrating how validation can prove its value throughout the production phase in terms of pre-validation, full validation and pre-release validation.
There are very few, if any, published accounts of practical expe rience with Speaker Verification as a means to provide secure access to telematics services. Yet, there is no reason to expect that Speaker Verification is very different from speech recogni tion, for which many deployed services have shown the need for close and intensive on-line monitoring during the time when the service becomes operational. In this paper we present our expe rience with a monitoring scheme for Speaker Verification dur ing the field test of a financial investment game. Many of the issues that were monitored were suggested by our experience with a semi-operational service, viz. free access to Directory Assistance for visually impaired. A newly developed enrolment procedure, that can flag potentially weak speaker models, is an essential part of the monitoring procedure.
Pseudo-Articulatory Representations are increasingly being used in work on speech synthesis and recognition. The value of such representations lies in their derivation from linguistic abstractions -they are based on articulatory idealizations used by linguists to describe speech. Iles [4] has demonstrated that using these representations it is possible to overcome the many-to-one problem in mapping articulatory configuration to acoustic signal. In this paper we show how the representations facilitate the details of speech processing, for both synthesis and recognition, and we give details of work in progress on recognition. The role of Pseudo-Articulatory Representations in the development of an integrated approach to synthesis and recognition is also discussed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.