Filmljudets funktioner i krigsfilm : En audio-visuell analys av Apocalypse Now och Saving Private Ryan

I denna uppsats har filmljudet i krigsfilmerna Apocalypse Now och Saving Private Ryan undersökts. Detta har gjorts för att försöka bidra med ökad förståelse för filmljudets användningsområde och funktioner, främst för filmerna i fråga, men även för krigsfilm rent generellt. Filmljud i denna kontext omfattar allt det ljud som finns i film, men utesluter dock all ickediegetisk musik. Båda filmerna har undersökts genom en audio-visuell analys. En sådan analys görs genom att detaljgranska båda filmernas ljud- och bildinnehåll var för sig, för att slutligen undersöka samma filmsekvens som helhet då ljudet och bilden satts ihop igen. Den audio-visuella analysmetod som nyttjats i uppsatsen är Michel Chions metod, Masking. De 30 minuter film som analyserades placerades sedan i olika filmljudzoner, där respektive filmljudzons ljudinnehåll bland annat visade vilka främsta huvudfunktioner somfilmljudet hade i dessa filmer. Dessa funktioner är till för att bibehålla åskådarens fokus och intresse, att skapa närhet till rollkaraktärerna, samt att tillföra en hög känsla av realism och närvaro. Intentionerna med filmljudet verkade vara att flytta åskådaren in i filmens verklighet, att låta åskådaren bli ett med filmen. Att återspegla denna känsla av realism, närvaro, fokus samt intresse, visade sig också vara de intentioner som funnits redan i de båda filmernas förproduktionsstadier. Detta bevisar att de lyckats åstadkomma det de eftersträvat. Men om filmljudet använts på samma sätt eller innehar samma funktioner i krigsfilm rent genrellt går inte att säga.I have for this bachelor’s thesis examined the movie sound of the classic warfare movies Apocalypse Now and Saving Private Ryan. This is an attempt to contribute to a more profound comprehension of the appliance and importance of movie sound. In this context movie sound implies all kinds of sounds within the movies, accept from non-diegetic music. These two movies have been examined by an audio-visual analysis. It's done by auditing the sound and picture content separately, and then combined to audit the same sequence as a whole. Michel Chion, which is the founder of this analysis, calls this method Masking. The sound in this 30 minute sequence was then divided into different zones, where every zone represented a certain main function. These functions are provided to create a stronger connection to the characters, sustain the viewers interest and bring a sense of realism and presence. It seems though the intention with the movies sound is to bring the viewers to the scene in hand, and let it become their reality. To mirror this sense of realism, presence, focus and interest, proves to be the intention from an early stage of the production. This bachelor’s thesis demonstrates a success in their endeavours. Although it can’t confirm whether the movie sound have been utilized in the same manner or if they posess the same functions to warefare movies in general.

Classification of Parkinson’s Disease using MultiPass Lvq,Logistic Model Tree,K-Star for Audio Data set : Classification of Parkinson Disease using Audio Dataset

Parkinson's disease (PD) is a degenerative illness whose cardinal symptoms include rigidity, tremor, and slowness of movement. In addition to its widely recognized effects PD can have a profound effect on speech and voice.The speech symptoms most commonly demonstrated by patients with PD are reduced vocal loudness, monopitch, disruptions of voice quality, and abnormally fast rate of speech. This cluster of speech symptoms is often termed Hypokinetic Dysarthria.The disease can be difficult to diagnose accurately, especially in its early stages, due to this reason, automatic techniques based on Artificial Intelligence should increase the diagnosing accuracy and to help the doctors make better decisions. The aim of the thesis work is to predict the PD based on the audio files collected from various patients.Audio files are preprocessed in order to attain the features.The preprocessed data contains 23 attributes and 195 instances. On an average there are six voice recordings per person, By using data compression technique such as Discrete Cosine Transform (DCT) number of instances can be minimized, after data compression, attribute selection is done using several WEKA build in methods such as ChiSquared, GainRatio, Infogain after identifying the important attributes, we evaluate attributes one by one by using stepwise regression.Based on the selected attributes we process in WEKA by using cost sensitive classifier with various algorithms like MultiPass LVQ, Logistic Model Tree(LMT), K-Star.The classified results shows on an average 80%.By using this features 95% approximate classification of PD is acheived.This shows that using the audio dataset, PD could be predicted with a higher level of accuracy.

Txtng as a replacement for standard written English : an attitude survey based on Age and Gender

Text messaging is a new form of writing, brought about by technological development in the last couple of decades. Mobile phone usage has increased rapidly worldwide and texting is now part of many people's everyday communcation. A large number of users send or receive texts which include some abbreviations and shortenings, commonly referred to as textspeak. This novel linguistic phenomenon is perceived by some with indifference and by others with aggravation. The following study examines attitudes towards this linguistic change from a gender and age perspective. The comparison between two groups show that the most conservative and least positive to change are young women. The analysis and discussion around this focuses on power, prestige and patterns.

The Concept of ’Selling/Buying’ in the Russian Linguistic Picture of the World : from standard to sub-standard

The thesis belongs to the field of lexical semantics studies, associated with describing the Russian linguistic world-image. The research focuses on the universal situation of purchase and sale as reflected in the Russian lexical standard and sub-standard. The work deals also with subjects related to the sphere of social linguistics: the social stratification of the language, the structure of sub-standard, etc. The thesis is a contribution to the description of the Russian linguistic world-image as well as to the further elaboration of the conceptional analysis method. The results are applicable in teaching Russian as a foreign language, particularly in lexis and Russian culture and mentality studies.

Filmljudets funktioner i dramafilm : En audio-visuell analys av filmen The King's Speech

Johansson, Fredrik (2012). Filmljudets funktioner i dramafilm – En audio-visuell analys av filmen The King´s Speech. Examensuppsats inom Ljudproduktion, Högskolan Dalarna, Akademin för språk och medier, Falun. I denna uppsats undersöktes filmljudet i dramafilmen The King´s Speech. Detta för att ta reda på vilka funktioner filmljudet fyller i de valda sekvenserna ur nämnda film, samt hur ljudet är placerat i filmens flerkanalsmix. Filmen granskades med hjälp av en audio-visuell analys. Denna metod går ut på att ljudet och bilden undersöks separat, för att sedan åter kombineras och analyseras som helhet. Den audio-visuella analysmetod som använts kommer från ljudteoretikern Michel Chion, och kallas Masking. Resultatet av den audio-visuella analysen pekade mot att ljudets huvudsakliga funktioner var att skapa en realistisk skildring av karaktärer och omgivningar, skapa en känsla av närvaro, samt att skapa och bibehålla olika perspektiv i den narrativa världen. Den stora majoriteten av ljud visade sig vara placerade i centerkanalen, medan främst ickediegetisk musik och ambiensljud var placerade i front- och surroundkanalerna. Detta kanalanvändande tycktes gynna de funna funktionerna, främst genom att bidra till känslan av närvaro och realism, genom att omsluta filmpubliken med ambienta ljud.

Game Audio in Audio Games : Towards a Theory on the Roles and Functions of Sound in Audio Games

For the past few decades, researchers have increased our understanding of how sound functions within various audio–visual media formats. With a different focus in mind, this study aims to identify the roles and functions of sound in relation to the game form Audio Games, in order to explore the potential of sound when acting as an autonomous narrative form. Because this is still a relatively unexplored research field, the main purpose of this study is to help establish a theoretical ground and stimulate further research within the field of audio games. By adopting an interdisciplinary approach to the topic, this research relies on theoretical studies, examinations of audio games and contact with the audio game community. In order to reveal the roles of sound, the gathered data is analyzed according to both a contextual and a functional perspective. The research shows that a distinction between the terms ‘function’ and ‘role’ is important when analyzing sound in digital games. The analysis therefore results in the identification of two analytical levels that help define the functions and roles of an entity within a social context, named the Functional and the Interfunctional levels. In addition to successfully identifying three main roles of sound within audio games—each describing the relationship between sound and the entities game system, player and virtual environment—many other issues are also addressed. Consequently, and in accordance with its purpose, this study provides a broad foundation for further research of sound in both audio games and video games.

First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.