Ingrid Kirschning

Learn More
Thanks to the advances in today's technology in terms of processing speed of computers, storage space and the management of sound and video devices, speech technology is a reality in almost any kind of computerized system. Speech applications are being used in personal computers, cellular phones, etc. This makes this interesting technology accessible to(More)
This paper presents an approach to representing emotions in synchronous text-based communication which facilitates setting, conveying and perceiving an intended mood in a continuing fashion. We posit that, while chatting, users typically remain in a continual mood for relatively extended periods of time, as compared to the instantaneous representation(More)
Some problems of "unlearning" were encountered when using Fahlman's Recurrent Cascade Correlation Learning Architecture (RCC) for phoneme recognition. In this paper we present a parallel-modular RCC. The original RCC is transformed into a modular RCC, trained with natural connectionist glue. This is done in order to concentrate the "knowledge" about a group(More)
This paper presents a novel approach for content-based image retrieval (CBIR) that provides the analysis of visual information using wavelet coefficients and similarity metrics. This approach has a better performance than well-known RedNew CBIR system based on image indexing and retrieval using neural networks. A principal goal of this report is precise(More)
This paper presents a new method for the verification of the correct pronunciation of spoken words. This process is based on speech recognition technology. It can be particularly useful when applied to the field of SLA (Second Language Acquisition) in learning environments or Computer-Aided Language Learning (CALL) systems, where the students can practice(More)
We have developed "Cronos", an environment that supports personal and public annotations on digital documents. Users of Cronos can also generate, view and share index cards that support scholarly work. A study of its initial use shows that Cronos has potential to effectively support research and scholarship conducted directly on Web documents.
In this paper a new method, called the Time-Slicing Paradigm, for the recognition of temporal patterns using neural networks is presented. This is a method for the analysis of the speech signal with the aim to achieve the recognition of connected speech with less preprocessing of the input signal than other existing neural networks. Along with the(More)
We developed a method called Time-Slicing [1] for the analysis of the speech signal. It enables a neural network to recognize connected speech as it comes, without having to fit the input signal into a fixed time-format, nor label or segment it phoneme by phoneme. The neural network produces an immediate hypothesis of the recognized phoneme and its size is(More)