1,068 research outputs found

    Using same-language machine translation to create alternative target sequences for text-to-speech synthesis

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    Modern speech synthesis systems attempt to produce speech utterances from an open domain of words. In some situations, the synthesiser will not have the appropriate units to pronounce some words or phrases accurately but it still must attempt to pronounce them. This paper presents a hybrid machine translation and unit selection speech synthesis system. The machine translation system was trained with English as the source and target language. Rather than the synthesiser only saying the input text as would happen in conventional synthesis systems, the synthesiser may say an alternative utterance with the same meaning. This method allows the synthesiser to overcome the problem of insufficient units in runtime

    Using Program Synthesis for Program Analysis

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    In this paper, we identify a fragment of second-order logic with restricted quantification that is expressive enough to capture numerous static analysis problems (e.g. safety proving, bug finding, termination and non-termination proving, superoptimisation). We call this fragment the {\it synthesis fragment}. Satisfiability of a formula in the synthesis fragment is decidable over finite domains; specifically the decision problem is NEXPTIME-complete. If a formula in this fragment is satisfiable, a solution consists of a satisfying assignment from the second order variables to \emph{functions over finite domains}. To concretely find these solutions, we synthesise \emph{programs} that compute the functions. Our program synthesis algorithm is complete for finite state programs, i.e. every \emph{function} over finite domains is computed by some \emph{program} that we can synthesise. We can therefore use our synthesiser as a decision procedure for the synthesis fragment of second-order logic, which in turn allows us to use it as a powerful backend for many program analysis tasks. To show the tractability of our approach, we evaluate the program synthesiser on several static analysis problems.Comment: 19 pages, to appear in LPAR 2015. arXiv admin note: text overlap with arXiv:1409.492

    Verifying privacy by little interaction and no process equivalence

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    While machine-assisted verification of classical security goals such as confidentiality and authentication is well-established, it is less mature for recent ones. Electronic voting protocols claim properties such as voter privacy. The most common modelling involves indistinguishability, and is specified via trace equivalence in cryptographic extensions of process calculi. However, it has shown restrictions. We describe a novel model, based on unlinkability between two pieces of information. Specifying it as an extension to the Inductive Method allows us to establish voter privacy without the need for approximation or session bounding. The two models and their latest specifications are contrasted

    GED - a generalised syntax editor : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Computer Science at Massey University

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    This thesis traces the development of a full-screen syntax-directed editor - a type of editor that operates on a program in terms of its syntactic tree structure instead of its sequential character representation. The editor is table-driven, reading as input an extended BNF syntax of the target language. It can therefore be used for any language whose syntax can be defined in EBNF. Print formatting information can be included with the syntactic definition to enable programs to be pretty-printed when they are displayed. The user is presented with a pretty-printed skeletal outline of a program with the currently selected construct highlighted and all required syntactic items provided by the editor. Any constructs with alternatives, such as "", which occurs in many languages, are initially denoted by a placeholder in the form of a non-terminal name (i.e. "") which is expanded when the user indicates which alternative is wanted. All symbols entered by the user are parsed immediately and any erroneous symbols rejected, making it impossible to create a syntactically incorrect program. The editor cannot detect semantic errors as no semantic information is available from the EBNF syntax. However the first use of all identifiers is flagged by the editor as an aid to the detection of undeclared identifiers. A "help" area at the bottom of the screen continuously displays a list of the correct next symbols and the syntactic definition of the currently selected program construct. This display, together with a multi-level "undo" command and the provision of a skeletal program by the editor, provides a way of exploring the various constructs in a programming language, while ensuring the syntactic correctness of the resultant program

    Close Copy Speech Synthesis for Speech Perception Testing

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    The present study is concerned with developing a speech synthesis subcomponent for perception testing in the context of evaluating cochlear implants in children. We provide a detailed requirements analysis, and develop a strategy for maximally high quality speech synthesis using Close Copy Speech synthesis techniques with a diphone based speech synthesiser, MBROLA. The close copy concept used in this work defines close copy as a function from a pair of speech signal recording and a phonemic annotation aligned with the recording into the pronunciation specification interface of the speech synthesiser. The design procedure has three phases: Manual Close Copy Speech (MCCS) synthesis as a ?best case gold standard?, in which the function is implemented manually as a preliminary step; Automatic Close Copy Speech (ACCS) synthesis, in which the steps taken in manual transformation are emulated by software; finally, Parametric Close Copy Speech (PCCS) synthesis, in which prosodic parameters are modifiable while retaining the diphones. This contribution reports on the MCCS and ACCS synthesis phases

    The design of sonically-enhanced widgets

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    This paper describes the design of user-interface widgets that include non-speech sound. Previous research has shown that the addition of sound can improve the usability of human–computer interfaces. However, there is little research to show where the best places are to add sound to improve usability. The approach described here is to integrate sound into widgets, the basic components of the human–computer interface. An overall structure for the integration of sound is presented. There are many problems with current graphical widgets and many of these are difficult to correct by using more graphics. This paper presents many of the standard graphical widgets and describes how sound can be added. It describes in detail usability problems with the widgets and then the non-speech sounds to overcome them. The non-speech sounds used are earcons. These sonically-enhanced widgets allow designers who are not sound experts to create interfaces that effectively improve usability and have coherent and consistent sounds

    Program Synthesis for Program Analysis

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    In this article, we propose a unified framework for designing static analysers based on program synthesis. For this purpose, we identify a fragment of second-order logic with restricted quantification that is expressive enough to model numerous static analysis problems (e.g., safety proving, bug finding, termination and non-termination proving, refactoring). As our focus is on programs that use bit-vectors, we build a decision procedure for this fragment over finite domains in the form of a program synthesiser. We provide instantiations of our framework for solving a diverse range of program verification tasks such as termination, non-termination, safety and bug finding, superoptimisation, and refactoring. Our experimental results show that our program synthesiser compares positively with specialised tools in each area as well as with general-purpose synthesisers

    Support for Learning Synthesiser Programming

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    When learning an instrument, students often like to emulate the sound and style of their favourite performers. The learning process takes many years of study and practice. In the case of synthesisers the vast parameter space involved can be daunting and unintuitive to the novice making it hard to define their desired sound and difficult to understand how it was achieved. Previous research has produced methods for automatically determining an appropriate parameter set to produce a desired sound but this can still require many parameters and does not explain or demonstrate the effect of particular parameters on the resulting sound. As a first step to solving this problem, this paper presents a new approach to searching the synthesiser parameter space to find a sound, reformulating it as a multi-objective optimisation problem (MOOP) where two competing objectives (closeness of perceived sonic match and number of parameters) are considered. As a proof-of-concept a pareto-optimal search algorithm (NSGA-II) is applied to CSound patches of varying complexity to generate a pareto-front of non-dominating (i.e. ”equally good”) solutions. The results offer insight into the extent to which the size and nature of parameter sets can be reduced whilst still retaining an acceptable degree of perceived sonic match between target and candidate sound
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