Insults, free speech and offensiveness

This article examines what is wrong with some expressive acts, ‘insults’. Their putative wrongfulness is distinguished from the causing of indirect harms, aggregated harms, contextual harms, and damaging misrepresentations. The article clarifies what insults are, making use of work by Neu and Austin, and argues that their wrongfulness cannot lie in the hurt that is caused to those at whom such acts are directed. Rather it must lie in what they seek to do, namely to denigrate the other. The causing of offence is at most evidence that an insult has been communicated; it is not independent grounds of proscription or constraint. The victim of an insult may know that she has been insulted but not accept or agree with the insult, and thereby submit to the insulter. Hence insults need not, as Waldron argues they do, occasion dignitary harms. They do not of themselves subvert their victims' equal moral status. The claim that hateful speech endorses inequality should not be conflated with a claim that such speech directly subverts equality.

Thus, ‘wounding words’ should not unduly trouble the liberal defender of free speech either on the grounds of preventing offence or on those of avoiding dignitary harms.

The interleukin 1beta gene promoter polymorphism (-511) acts as a risk factor for psychosis in Alzheimer's dementia

The explanation for why some patients develop psychotic change in Alzheimer's disease (AD) is unclear. "Psychosis-modifier genes" may act in the setting of neurodegeneration to produce AD plus psychosis in a similar way to how genetic modulation during neurodevelopment leads to schizophrenia. Because there is increasing interest in the common disruption of cytokine pathways seen in both AD and schizophrenia, we tested the association between the functional interleukin-1beta -511 promoter polymorphism with delusions and hallucinations in AD. Significant associations between psychotic symptoms and the CC genotype (p = 0.001 - p = 0.043) and C allele (p = 0.014 vs p = 0.048) were found, thus confirming the previously noted increased risk in schizophrenia.

Emotional speech: towards a new generation of databases

Research on speech and emotion is moving from a period of exploratory research into one where there is a prospect of substantial applications, notably in human-computer interaction. Progress in the area relies heavily on the development of appropriate databases. This paper addresses the issues that need to be considered in developing databases of emotional speech, and shows how the challenge of developing apropriate databases is being addressed in three major recent projects - the Belfast project, the Reading-Leeds project and the CREST-ESP project. From these and other studies the paper draws together the tools and methods that have been developed, addresses the problems that arise and indicates the future directions for the development of emotional speech databases.

Speech Recognition with unknown partial feature corruption - a review of the union model

This paper provides a summary of our studies on robust speech recognition based on a new statistical approach – the probabilistic union model. We consider speech recognition given that part of the acoustic features may be corrupted by noise. The union model is a method for basing the recognition on the clean part of the features, thereby reducing the effect of the noise on recognition. To this end, the union model is similar to the missing feature method. However, the two methods achieve this end through different routes. The missing feature method usually requires the identity of the noisy data for noise removal, while the union model combines the local features based on the union of random events, to reduce the dependence of the model on information about the noise. We previously investigated the applications of the union model to speech recognition involving unknown partial corruption in frequency band, in time duration, and in feature streams. Additionally, a combination of the union model with conventional noise-reduction techniques was studied, as a means of dealing with a mixture of known or trainable noise and unknown unexpected noise. In this paper, a unified review, in the context of dealing with unknown partial feature corruption, is provided into each of these applications, giving the appropriate theory and implementation algorithms, along with an experimental evaluation.