981 resultados para Free speech
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Model-based approaches to handling additive background noise and channel distortion, such as Vector Taylor Series (VTS), have been intensively studied and extended in a number of ways. In previous work, VTS has been extended to handle both reverberant and background noise, yielding the Reverberant VTS (RVTS) scheme. In this work, rather than assuming the observation vector is generated by the reverberation of a sequence of background noise corrupted speech vectors, as in RVTS, the observation vector is modelled as a superposition of the background noise and the reverberation of clean speech. This yields a new compensation scheme RVTS Joint (RVTSJ), which allows an easy formulation for joint estimation of both additive and reverberation noise parameters. These two compensation schemes were evaluated and compared on a simulated reverberant noise corrupted AURORA4 task. Both yielded large gains over VTS baseline system, with RVTSJ outperforming the previous RVTS scheme. © 2011 IEEE.
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This speech is given to the United States House of Representatives. Hon. William Elliot gives a persuasive argument for why he will be voting against the senate amendment for free coinage of silver. He defines free coinage of silver and he describes fifty-cent dollar. He discusses the fall in the price of products and provides causation.
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Imperfect: front cover unhinged.
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Presented by Mr. Gallinger and ordered printed, April 22, 1909.
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Purpose: The classic study of Sumby and Pollack (1954, JASA, 26(2), 212-215) demonstrated that visual information aided speech intelligibility under noisy auditory conditions. Their work showed that visual information is especially useful under low signal-to-noise conditions where the auditory signal leaves greater margins for improvement. We investigated whether simulated cataracts interfered with the ability of participants to use visual cues to help disambiguate the auditory signal in the presence of auditory noise. Methods: Participants in the study were screened to ensure normal visual acuity (mean of 20/20) and normal hearing (auditory threshold ≤ 20 dB HL). Speech intelligibility was tested under an auditory only condition and two visual conditions: normal vision and simulated cataracts. The light scattering effects of cataracts were imitated using cataract-simulating filters. Participants wore blacked-out glasses in the auditory only condition and lens-free frames in the normal auditory-visual condition. Individual sentences were spoken by a live speaker in the presence of prerecorded four-person background babble set to a speech-to-noise ratio (SNR) of -16 dB. The SNR was determined in a preliminary experiment to support 50% correct identification of sentence under the auditory only conditions. The speaker was trained to match the rate, intensity and inflections of a prerecorded audio track of everyday speech sentences. The speaker was blind to the visual conditions of the participant to control for bias.Participants’ speech intelligibility was measured by comparing the accuracy of their written account of what they believed the speaker to have said to the actual spoken sentence. Results: Relative to the normal vision condition, speech intelligibility was significantly poorer when participants wore simulated catarcts. Conclusions: The results suggest that cataracts may interfere with the acquisition of visual cues to speech perception.
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Automatic Speech Recognition (ASR) has matured into a technology which is becoming more common in our everyday lives, and is emerging as a necessity to minimise driver distraction when operating in-car systems such as navigation and infotainment. In “noise-free” environments, word recognition performance of these systems has been shown to approach 100%, however this performance degrades rapidly as the level of background noise is increased. Speech enhancement is a popular method for making ASR systems more ro- bust. Single-channel spectral subtraction was originally designed to improve hu- man speech intelligibility and many attempts have been made to optimise this algorithm in terms of signal-based metrics such as maximised Signal-to-Noise Ratio (SNR) or minimised speech distortion. Such metrics are used to assess en- hancement performance for intelligibility not speech recognition, therefore mak- ing them sub-optimal ASR applications. This research investigates two methods for closely coupling subtractive-type enhancement algorithms with ASR: (a) a computationally-efficient Mel-filterbank noise subtraction technique based on likelihood-maximisation (LIMA), and (b) in- troducing phase spectrum information to enable spectral subtraction in the com- plex frequency domain. Likelihood-maximisation uses gradient-descent to optimise parameters of the enhancement algorithm to best fit the acoustic speech model given a word se- quence known a priori. Whilst this technique is shown to improve the ASR word accuracy performance, it is also identified to be particularly sensitive to non-noise mismatches between the training and testing data. Phase information has long been ignored in spectral subtraction as it is deemed to have little effect on human intelligibility. In this work it is shown that phase information is important in obtaining highly accurate estimates of clean speech magnitudes which are typically used in ASR feature extraction. Phase Estimation via Delay Projection is proposed based on the stationarity of sinusoidal signals, and demonstrates the potential to produce improvements in ASR word accuracy in a wide range of SNR. Throughout the dissertation, consideration is given to practical implemen- tation in vehicular environments which resulted in two novel contributions – a LIMA framework which takes advantage of the grounding procedure common to speech dialogue systems, and a resource-saving formulation of frequency-domain spectral subtraction for realisation in field-programmable gate array hardware. The techniques proposed in this dissertation were evaluated using the Aus- tralian English In-Car Speech Corpus which was collected as part of this work. This database is the first of its kind within Australia and captures real in-car speech of 50 native Australian speakers in seven driving conditions common to Australian environments.
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For most people, speech production is relatively effortless and error-free. Yet it has long been recognized that we need some type of control over what we are currently saying and what we plan to say. Precisely how we monitor our internal and external speech has been a topic of research interest for several decades. The predominant approach in psycholinguistics has assumed monitoring of both is accomplished via systems responsible for comprehending others' speech. This special topic aimed to broaden the field, firstly by examining proposals that speech production might also engage more general systems, such as those involved in action monitoring. A second aim was to examine proposals for a production-specific, internal monitor. Both aims require that we also specify the nature of the representations subject to monitoring.
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Oral cancer ranks among the 10 most common cancers worldwide. Since it is commonly diagnosed at locally advanced stage, curing the cancer demands extensive tissue resection. The emergent defect is reconstructed generally with a free flap transfer. Repair of the upper aerodigestive track with maintenance of its multiform activities is challenging. The aim of the study was to extract comprehensive treatment outcomes for patients having undergone microvascular free flap transfer because of large oral cavity or pharyngeal cancer. Ninety-four patients were analyzed for postoperative survival and complications. Forty-four patients were followed-up and analyzed for functional outcome, which was determined in terms of quality of life, speech, swallowing, and intraoral sensation. Quality of life was assessed using the University of Washington Head and Neck Questionnaire. Speech was analyzed for aerodynamic parameters and for nasal acoustic energy, as well as perceptually for articulatory proficiency, voice quality, and intelligibility. Videofluorography was performed to determine the swallowing ability. Intraoral sensation was measured by moving 2-point discrimination. The 3-year overall survival was over 40%. The 1-year disease-free survival was 43%. Postoperative complications arose in over half of the patients. Flap success rate was high. Perioperative mortality varied between 2% and 11%. Unemployment and heavy drinking were the strongest predictors of survival. Sociodemographic factors were found to associate with quality of life. The global quality of life score deteriorated and did not return to the preoperative level. Significant reduction was detectable in the domains measuring chewing and speech, and in appearance and shoulder function. The basic elements necessary for normal speech were maintained. Speech intelligibility reduced and was related to the misarticulations of the /r/ and /s/ phonemes. Deviant /r/ and /s/ persisted in most patients. Hoarseness and hypernasality occurred infrequently. One year postoperatively, 98% of the patients had achieved oral nutrition and half of them were on a regular masticated diet. Overt and silent aspiration was encountered throughout the follow-up. At 12-month swallow test, 44% of the patients aspirated, 70% of whom silently. Of these patients, 15% presented with pulmonary changes referring to aspiration. Intraoral sensation weakened but was unrelated to oral functions. The results provide new data for oral reconstructions and highlight the importance of the functional outcome of the treatment for an oral cancer patient. The mouth and the pharynx encompass a unit of utmost functional complexity. Surgery should continue to make progress in this area, and methods that lead to good function should be developed. Operational outcome should always be evaluated in terms of function.
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In late 2010, the online nonprofit media organization WikiLeaks published classified documents detailing correspondence between the U.S. State Department and its diplomatic missions around the world, numbering around 250,000 cables. These diplomatic cables contained classified information with comments on world leaders, foreign states, and various international and domestic issues. Negative reactions to the publication of these cables came from both the U.S. political class (which was generally condemnatory of WikiLeaks, invoking national security concerns and the jeopardizing of U.S. interests abroad) and the corporate world, with various companies ceasing to continue to provide services to WikiLeaks despite no legal measure (e.g., a court injunction) forcing them to do so. This article focuses on the legal remedies available to WikiLeaks against this corporate suppression of its speech in the U.S. and Europe since these are the two principle arenas in which the actors concerned are operating. The transatlantic legal protection of free expression will be considered, yet, as will be explained in greater detail, the legal conception of this constitutional and fundamental right comes from a time when the state posed the greater threat to freedom. As a result, it is not generally enforceable against private, non-state entities interfering with speech and expression which is the case here. Other areas of law, namely antitrust/competition, contract and tort will then be examined to determine whether WikiLeaks and its partners can attempt to enforce their right indirectly through these other means. Finally, there will be some concluding thoughts about the implications of the corporate response to the WikiLeaks embassy cables leak for freedom of expression online.
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Using an entropy argument, it is shown that stochastic context-free grammars (SCFG's) can model sources with hidden branching processes more efficiently than stochastic regular grammars (or equivalently HMM's). However, the automatic estimation of SCFG's using the Inside-Outside algorithm is limited in practice by its O(n3) complexity. In this paper, a novel pre-training algorithm is described which can give significant computational savings. Also, the need for controlling the way that non-terminals are allocated to hidden processes is discussed and a solution is presented in the form of a grammar minimization procedure. © 1990.
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VODIS II, a research system in which recognition is based on the conventional one-pass connected-word algorithm extended in two ways, is described. Syntactic constraints can now be applied directly via context-free-grammar rules, and the algorithm generates a lattice of candidate word matches rather than a single globally optimal sequence. This lattice is then processed by a chart parser and an intelligent dialogue controller to obtain the most plausible interpretations of the input. A key feature of the VODIS II architecture is that the concept of an abstract word model allows the system to be used with different pattern-matching technologies and hardware. The current system implements the word models on a real-time dynamic-time-warping recognizer.
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This paper describes two applications in speech recognition of the use of stochastic context-free grammars (SCFGs) trained automatically via the Inside-Outside Algorithm. First, SCFGs are used to model VQ encoded speech for isolated word recognition and are compared directly to HMMs used for the same task. It is shown that SCFGs can model this low-level VQ data accurately and that a regular grammar based pre-training algorithm is effective both for reducing training time and obtaining robust solutions. Second, an SCFG is inferred from a transcription of the speech used to train a phoneme-based recognizer in an attempt to model phonotactic constraints. When used as a language model, this SCFG gives improved performance over a comparable regular grammar or bigram. © 1991.
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Diane Rowland, Griping, Bitching and Speaking Your Mind: Defamation and Free Expression on the Internet, Pennsylvania State Law Review Symposium Issue 110, no. 3 (2006): 519?538; RAE2008
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It is shown that under certain conditions it is possible to obtain a good speech estimate from noise without requiring noise estimation. We study an implementation of the theory, namely wide matching, for speech enhancement. The new approach performs sentence-wide joint speech segment estimation subject to maximum recognizability to gain noise robustness. Experiments have been conducted to evaluate the new approach with variable noises and SNRs from -5 dB to noise free. It is shown that the new approach, without any estimation of the noise, significantly outperformed conventional methods in the low SNR conditions while retaining comparable performance in the high SNR conditions. It is further suggested that the wide matching and deep learning approaches can be combined towards a highly robust and accurate speech estimator.