Indeterminate Sentences for the Severely Personality Disordered

In line with recent incapacitative efforts aimed at dealing with dangerous people in the community, the Government has proposed a new indeterminate sentence to deal with the current gap in the law which exists in relation to dangerous individuals with untreatable severe personality disorders. However, these new measures have serious civil liberty implications and are largely unworkable in practice. It is suggested that rather than introducing these new powers it would be better to consider amending deficiencies which exist in the criminal justice and mental health systems in respect of the management of violent and sexual offenders.

Assembling a consistent set of sentences in relational probabilistic logic with stochastic independence

We examine the representation of judgements of stochastic independence in probabilistic logics. We focus on a relational logic where (i) judgements of stochastic independence are encoded by directed acyclic graphs, and (ii) probabilistic assessments are flexible in the sense that they are not required to specify a single probability measure. We discuss issues of knowledge representation and inference that arise from our particular combination of graphs, stochastic independence, logical formulas and probabilistic assessments.

Mentally disordered offenders and the European Court of Human Rights

This article presents the findings from a study of cases taken to the European Court of Human Rights by mentally disordered offenders. The issues raised include the problems raised by indeterminate sentences, the use of detention for preventive purposes, and debates about treatment. The countries represented are Belgium, Norway, Poland, the Netherlands, Russia and the United Kingdom.

‘Risk, Politics and the ‘Scientification’ of Political Judgement: Prisoner Release and Conflict Transformation in Northern Ireland’

Drawing on research in Northern Ireland into the process of release under the Belfast/Good Friday Agreement, this article explores the identification and classification of risk in relation to prisoners released early under the Sentences (NI) Act. The main argument is that conflict, post-conflict and transitional conditions expose more starkly the political underpinnings of risk-management strategy and the article demonstrates the particular variant of Politicized Risk Assessment (PRA) recently used in the release of prisoners in Northern Ireland

Teaching stylistics: analysing cohesion and narrative structure in a short story by Ernest Hemingway

The main aim of this article is to propose an exercise in stylistic analysis which can be employed in the teaching of English language. It details the design and results of a workshop activity on narrative carried out with undergraduates in a university department of English. The methods proposed are intended to enable students to obtain insights into aspects of cohesion and narrative structure; insights, it is suggested, which are not as readily obtainable through more traditional techniques of stylistic analysis. The text chosen for analysis is a short story by Ernest Hemingway comprising only 11 sentences. A jumbled version of this story is presented to students who are asked to assemble a cohesive and well-formed version of the story. Their (re)constructions are then compared with the original Hemingway version. Much interest, it is argued, lies in the ways in which the students justify their own versions in terms of their expectations about well-formedness in narrative. The activity is also intended to encourage students to see literary texts as a valuable means of providing insights into the subtleties of linguistic form and function.

Keeping it in the Family: Surviving Political Exile, 1870-1917

A sentence of exile was a regular feature of the Russian revolutionary’s underground career. In order to survive this punishment and continue their struggle against Tsarism, revolutionaries relied on help from their fellow exiles, their party, the Political Red Cross and, often, their families. Historians have rarely acknowledged the role of kin in supporting the revolutionary movement and very few studies have noted the attempts by families to mitigate the worst aspects of a sentence of exile. This article explores the ways in which spouses and siblings, parents and children obtained concessions from the Tsarist authorities regarding their loved ones’ sentences of exile, helped off-set the poverty to which many exiles were reduced, and, above all, combated the sense of loneliness and depression to which those in exile were exposed. This article argues that such familial support had a collective and positive impact on revolutionaries’ experience of exile. More broadly it provides an illuminating case study of the blurred space between public and private which the revolutionary occupied and highlights the way in which the movement depended on help from sympathisers and family members in order to function effectively on a daily basis.

Analysis of information leakage from encrypted Skype conversations

Voice over IP (VoIP) has experienced a tremendous growth over the last few years and is now widely used among the population and for business purposes. The security of such VoIP systems is often assumed, creating a false sense of privacy. This paper investigates in detail the leakage of information from Skype, a widely used and protected VoIP application. Experiments have shown that isolated phonemes can be classified and given sentences identified. By using the dynamic time warping (DTW) algorithm, frequently used in speech processing, an accuracy of 60% can be reached. The results can be further improved by choosing specific training data and reach an accuracy of 83% under specific conditions. The initial results being speaker dependent, an approach involving the Kalman filter is proposed to extract the kernel of all training signals.

ASR emotional speech: Clarifying the issues and enhancing performance

There are multiple reasons to expect that recognising the verbal content of emotional speech will be a difficult problem, and recognition rates reported in the literature are in fact low. Including information about prosody improves recognition rate for emotions simulated by actors, but its relevance to the freer patterns of spontaneous speech is unproven. This paper shows that recognition rate for spontaneous emotionally coloured speech can be improved by using a language model based on increased representation of emotional utterances. The models are derived by adapting an already existing corpus, the British National Corpus (BNC). An emotional lexicon is used to identify emotionally coloured words, and sentences containing these words are recombined with the BNC to form a corpus with a raised proportion of emotional material. Using a language model based on that technique improves recognition rate by about 20%. (c) 2005 Elsevier Ltd. All rights reserved.

Notes from Some Small Countries: A Study of the 'New Punitiveness' in Ireland, Scotland and New Zealand

In recent years there has been a remarkable surge of interest in the concept of punitiveness in theoretical criminology. Accounts serve to emphasise rupture over continuity, drawing attention to the increased focus on managerialism, risk and expressive penal policies in countries such as England and the US. Criticisms of these accounts have drawn attention to the weak empirical base for such assertions and the continued relevance of local cultural, historical and political conditions in mediating the effect of more punitive trends. In light of the relative neglect of smaller jurisdictions in this literature it was decided to locate these debates in three small common law jurisdictions, namely, Ireland, Scotland and New Zealand over the period 1976-2006 with a view to assessing the empirical evidence for penal change. This was done using a broader definition of punitiveness than normally employed incorporating indices relating to the ‘front end’ (eg police powers) as well as the ‘back end’ (eg prison and probation) of the criminal justice system. Data were collected on the three case studies using a multi-method approach involving examination of extensive quantitative data, interviews with key criminal justice stakeholders and documentary analysis. The data provide some support for the ‘new punitiveness’ thesis in these countries through a pattern of increased legislative activity aimed at controlling violent and sexual offenders and significant increases in the lengths of sentences imposed. However, analysis of qualitative data and a larger number of variables reveals distinctly different patterns of punitiveness over the thirty year period in the three countries. It is argued that the study holds important lessons for comparative criminology into the ‘new punitiveness’. There is a need for qualitative as well as quantitative data; for multiple rather than singular indices across a wide range of areas (juvenile justice, prison conditions, etc); and for ‘front end’ as well as ‘back end’ indices.

Reconceptualising Penality: A comparative perspective on punitiveness in Ireland, Scotland and New Zealand

Drastic increases in the use of imprisonment; the introduction of ‘three strikes’ laws and mandatory sentences; restrictions on parole - all of these developments appear to signify a new, harsher era or ‘punitive turn’. Yet these features of criminal justice are not universally present in all Western countries. Drawing on empirical data, Hamilton examines the prevalence of harsher penal policies in Ireland, Scotland and New Zealand, thereby demonstrating the utility of viewing criminal justice from the perspective of smaller jurisdictions.

This highly innovative book is thoroughly critical of the way in which punitiveness is currently measured by leading criminologists. It is essential reading for students and scholars of criminology, penology, criminal justice and socio-legal studies, as well as criminal lawyers and practitioners.

A Corpus-Based Approach to Speech Enhancement from Nonstationary Noise

Temporal dynamics and speaker characteristics are two important features of speech that distinguish speech from noise. In this paper, we propose a method to maximally extract these two features of speech for speech enhancement. We demonstrate that this can reduce the requirement for prior information about the noise, which can be difficult to estimate for fast-varying noise. Given noisy speech, the new approach estimates clean speech by recognizing long segments of the clean speech as whole units. In the recognition, clean speech sentences, taken from a speech corpus, are used as examples. Matching segments are identified between the noisy sentence and the corpus sentences. The estimate is formed by using the longest matching segments found in the corpus sentences. Longer speech segments as whole units contain more distinct dynamics and richer speaker characteristics, and can be identified more accurately from noise than shorter speech segments. Therefore, estimation based on the longest recognized segments increases the noise immunity and hence the estimation accuracy. The new approach consists of a statistical model to represent up to sentence-long temporal dynamics in the corpus speech, and an algorithm to identify the longest matching segments between the noisy sentence and the corpus sentences. The algorithm is made more robust to noise uncertainty by introducing missing-feature based noise compensation into the corpus sentences. Experiments have been conducted on the TIMIT database for speech enhancement from various types of nonstationary noise including song, music, and crosstalk speech. The new approach has shown improved performance over conventional enhancement algorithms in both objective and subjective evaluations.

Combining missing-feature theory, speech enhancement, and speaker-dependent/-independent modeling for speech separation

This paper considers the separation and recognition of overlapped speech sentences assuming single-channel observation. A system based on a combination of several different techniques is proposed. The system uses a missing-feature approach for improving crosstalk/noise robustness, a Wiener filter for speech enhancement, hidden Markov models for speech reconstruction, and speaker-dependent/-independent modeling for speaker and speech recognition. We develop the system on the Speech Separation Challenge database, involving a task of separating and recognizing two mixing sentences without assuming advanced knowledge about the identity of the speakers nor about the signal-to-noise ratio. The paper is an extended version of a previous conference paper submitted for the challenge.