Representation Analysis Methods to Model Context for Speech Technology

Speech technology has developed to levels equivalent with human parity through the use of deep neural networks. However, it is unclear how the learned dependencies within these networks can be attributed to metrics such as recognition performance. This research focuses on strategies to interpret and exploit these learned context dependencies to improve speech recognition models. Context dependency analysis had not yet been explored for speech recognition networks. In order to highlight and observe dependent representations within speech recognition models, a novel analysis framework is proposed. This analysis framework uses statistical correlation indexes to compute the coefficiency between neural representations. By comparing the coefficiency of neural representations between models using different approaches, it is possible to observe specific context dependencies within network layers. By providing insights on context dependencies it is then possible to adapt modelling approaches to become more computationally efficient and improve recognition performance. Here the performance of End-to-End speech recognition models are analysed, providing insights on the acoustic and language modelling context dependencies. The modelling approach for a speaker recognition task is adapted to exploit acoustic context dependencies and reach comparable performance with the state-of-the-art methods, reaching 2.89% equal error rate using the Voxceleb1 training and test sets with 50% of the parameters. Furthermore, empirical analysis of the role of acoustic context for speech emotion recognition modelling revealed that emotion cues are presented as a distributed event. These analyses and results for speech recognition applications aim to provide objective direction for future development of automatic speech recognition systems

Rehabilitation versus surgical reconstruction for non-acute anterior cruciate ligament injury (ACL SNNAP): a pragmatic randomised controlled trial

BackgroundAnterior cruciate ligament (ACL) rupture is a common debilitating injury that can cause instability of the knee. We aimed to investigate the best management strategy between reconstructive surgery and non-surgical treatment for patients with a non-acute ACL injury and persistent symptoms of instability.MethodsWe did a pragmatic, multicentre, superiority, randomised controlled trial in 29 secondary care National Health Service orthopaedic units in the UK. Patients with symptomatic knee problems (instability) consistent with an ACL injury were eligible. We excluded patients with meniscal pathology with characteristics that indicate immediate surgery. Patients were randomly assigned (1:1) by computer to either surgery (reconstruction) or rehabilitation (physiotherapy but with subsequent reconstruction permitted if instability persisted after treatment), stratified by site and baseline Knee Injury and Osteoarthritis Outcome Score—4 domain version (KOOS4). This management design represented normal practice. The primary outcome was KOOS4 at 18 months after randomisation. The principal analyses were intention-to-treat based, with KOOS4 results analysed using linear regression. This trial is registered with ISRCTN, ISRCTN10110685, and ClinicalTrials.gov, NCT02980367.FindingsBetween Feb 1, 2017, and April 12, 2020, we recruited 316 patients. 156 (49%) participants were randomly assigned to the surgical reconstruction group and 160 (51%) to the rehabilitation group. Mean KOOS4 at 18 months was 73·0 (SD 18·3) in the surgical group and 64·6 (21·6) in the rehabilitation group. The adjusted mean difference was 7·9 (95% CI 2·5–13·2; p=0·0053) in favour of surgical management. 65 (41%) of 160 patients allocated to rehabilitation underwent subsequent surgery according to protocol within 18 months. 43 (28%) of 156 patients allocated to surgery did not receive their allocated treatment. We found no differences between groups in the proportion of intervention-related complications.InterpretationSurgical reconstruction as a management strategy for patients with non-acute ACL injury with persistent symptoms of instability was clinically superior and more cost-effective in comparison with rehabilitation management

I neologismi autoriali e la loro traduzione nella saga di Harry Potter: il caso dello spagnolo e dell'italiano

L'elaborato analizza i neologismi autoriali creati nella saga di Harry Potter, dapprima nella loro versione originale studiando i meccanismi di formazione di neologismi più utilizzati. In seguito, i neologismi originali vengono messi a confronto con le loro traduzioni in italiano e spagnolo, studiando le strategie traduttive messe in atto dai rispettivi team di traduttori. I dati analizzati vengono poi ricondotti alla teoria della traduzione della letteratura per l'infanzia e ai distinti filoni individuabili nei due Paesi

“That was a touching exhortation, dear Armadillo”: English translation of the graphic novel LA PROFEZIA DELL’ARMADILLO by Zerocalcare

The aim of this work is to present a translation into English of the graphic novel La Profezia dell’Armadillo by Zerocalcare, published in 2012 by Bao Publishing. It is worth specifying that the translation proposed in this dissertation is specifically targeted at the North American market. The first chapter offers a theoretical framework by giving a definition of the medium of comics and the medium of the graphic novel. It then briefly outlines the history of comics in the United States, and how the development of comics has led to the modern graphic novel. The second chapter outlines the development of comics in Italy, with a particular emphasis on those stages that have had a strong influence on the modern graphic novel. A number of the most important Italian graphic novelists are also presented: Vanna Vinci, Davide Toffolo, and Gipi. The third chapter is dedicated entirely to Zerocalcare and La Profezia dell’Armadillo. It first gives a brief biographical outline on the author, his recent works and his success. Later, the narrative, linguistic, and stylistic style of the graphic novel is analyzed. The fourth chapter presents an in-depth comment on the translation proposed. The most prominent and challenging translation problems are divided into three categories (problems relating to the comics medium, to the language, or to cultural references) and analyzed. The appendix of the dissertation includes two interviews carried out by email: the first is to Zerocalcare, while the second is to Michele Foschini, the CEO of Bao Publishing. The appendix also includes the complete translation of the graphic novel

Insights on Neural Representations for End-to-End Speech Recognition

End-to-end automatic speech recognition (ASR) models aim to learn a generalised speech representation. However, there are limited tools available to understand the internal functions and the effect of hierarchical dependencies within the model architecture. It is crucial to understand the correlations between the layer-wise representations, to derive insights on the relationship between neural representations and performance. Previous investigations of network similarities using correlation analysis techniques have not been explored for End-to-End ASR models. This paper analyses and explores the internal dynamics between layers during training with CNN, LSTM and Transformer based approaches using Canonical correlation analysis (CCA) and centered kernel alignment (CKA) for the experiments. It was found that neural representations within CNN layers exhibit hierarchical correlation dependencies as layer depth increases but this is mostly limited to cases where neural representation correlates more closely. This behaviour is not observed in LSTM architecture, however there is a bottom-up pattern observed across the training process, while Transformer encoder layers exhibit irregular coefficiency correlation as neural depth increases. Altogether, these results provide new insights into the role that neural architectures have upon speech recognition performance. More specifically, these techniques can be used as indicators to build better performing speech recognition models.Comment: Submitted to Interspeech 202