996 resultados para Political speech


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Modeling nonlinear systems using Volterra series is a century old method but practical realizations were hampered by inadequate hardware to handle the increased computational complexity stemming from its use. But interest is renewed recently, in designing and implementing filters which can model much of the polynomial nonlinearities inherent in practical systems. The key advantage in resorting to Volterra power series for this purpose is that nonlinear filters so designed can be made to work in parallel with the existing LTI systems, yielding improved performance. This paper describes the inclusion of a quadratic predictor (with nonlinearity order 2) with a linear predictor in an analog source coding system. Analog coding schemes generally ignore the source generation mechanisms but focuses on high fidelity reconstruction at the receiver. The widely used method of differential pnlse code modulation (DPCM) for speech transmission uses a linear predictor to estimate the next possible value of the input speech signal. But this linear system do not account for the inherent nonlinearities in speech signals arising out of multiple reflections in the vocal tract. So a quadratic predictor is designed and implemented in parallel with the linear predictor to yield improved mean square error performance. The augmented speech coder is tested on speech signals transmitted over an additive white gaussian noise (AWGN) channel.

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This paper discusses the implementation details of a child friendly, good quality, English text-to-speech (TTS) system that is phoneme-based, concatenative, easy to set up and use with little memory. Direct waveform concatenation and linear prediction coding (LPC) are used. Most existing TTS systems are unit-selection based, which use standard speech databases available in neutral adult voices.Here reduced memory is achieved by the concatenation of phonemes and by replacing phonetic wave files with their LPC coefficients. Linguistic analysis was used to reduce the algorithmic complexity instead of signal processing techniques. Sufficient degree of customization and generalization catering to the needs of the child user had been included through the provision for vocabulary and voice selection to suit the requisites of the child. Prosody had also been incorporated. This inexpensive TTS systemwas implemented inMATLAB, with the synthesis presented by means of a graphical user interface (GUI), thus making it child friendly. This can be used not only as an interesting language learning aid for the normal child but it also serves as a speech aid to the vocally disabled child. The quality of the synthesized speech was evaluated using the mean opinion score (MOS).

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This paper describes certain findings of intonation and intensity study of emotive speech with the minimal use of signal processing algorithms. This study was based on six basic emotions and the neutral, elicited from 1660 English utterances obtained from the speech recordings of six Indian women. The correctness of the emotional content was verified through perceptual listening tests. Marked similarity was noted among pitch contours of like-worded, positive valence emotions, though no such similarity was observed among the four negative valence emotional expressions. The intensity patterns were also studied. The results of the study were validated using arbitrary television recordings for four emotions. The findings are useful to technical researchers, social psychologists and to the common man interested in the dynamics of vocal expression of emotions

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Speech is the primary, most prominent and convenient means of communication in audible language. Through speech, people can express their thoughts, feelings or perceptions by the articulation of words. Human speech is a complex signal which is non stationary in nature. It consists of immensely rich information about the words spoken, accent, attitude of the speaker, expression, intention, sex, emotion as well as style. The main objective of Automatic Speech Recognition (ASR) is to identify whatever people speak by means of computer algorithms. This enables people to communicate with a computer in a natural spoken language. Automatic recognition of speech by machines has been one of the most exciting, significant and challenging areas of research in the field of signal processing over the past five to six decades. Despite the developments and intensive research done in this area, the performance of ASR is still lower than that of speech recognition by humans and is yet to achieve a completely reliable performance level. The main objective of this thesis is to develop an efficient speech recognition system for recognising speaker independent isolated words in Malayalam.

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HINDI

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This study addresses the effectivity of the Anti-Bias approach and training methodology as a pedagogical political strategy to challenge oppression among student groups in the cities of Bombay and Berlin. The Anti-Bias trainings conducted within the framework of this study also become the medium through which the perpetuation of oppressive structures by students within and outside the school is investigated. Empirical data from predominantly qualitative investigations in four secondary schools, two each in Bombay and Berlin, is studied and analysed on the basis of theoretical understandings of prejudice, discrimination and identity. This study builds on insights offered by previous research on prejudices and evaluations of anti-bias and diversity interventions, where the lack of sufficient research and thorough evaluations testing impact has been identified (Levy Paluck, 2006). The theoretical framework suggests that prejudices and discriminatory practices are learnt and performed by individuals over the years by way of pre-existing discourses, and that behaviour and practices can be unlearnt through a multi-step process. It proposes that the discursive practices of students contribute to the constitution of their viable selves and in the constitution of ‘others’. Drawing on this framework, the study demonstrates how student-subjects in Bombay and Berlin perpetuate oppressive discourses by performing their identities and performing identities onto ‘others’. Such performative constitution opens up the agency of the individual, disclosing the shifting and dynamic nature of identities. The Anti-Bias approach is posited as an alternative to oppressive discourses and a vehicle that encourages and assists the agency of individuals. The theoretical framework, which brings together a psychological approach to prejudice, a structural approach to discrimination and a poststructural approach to identity, facilitates the analysis of the perpetuation of dominant discourses by the students, as well as how they negotiate their way through familiar norms and discourses. Group discussions and interviews a year after the respective trainings serve to evaluate the agency of the students and the extent to which the training impacted on their perceptions, attitudes and behavioural practices. The study reveals the recurrence of the themes race, religion, gender and sexuality in the representational practices of the students groups in Berlin and Bombay. It demonstrates how students in this study not only perform, but also negotiate and resist oppressive structures. Of particular importance is the role of the school: When schools offer no spaces for discussion, debate and action on contemporary social issues, learning can neither be put into practice nor take on a positive, transformative form. In such cases, agency and resistance is limited and interventionist actions yield little. This study reports the potential of the Anti-Bias approach and training as a tool of political education and action in education. It demonstrates that a single training can initiate change but sustaining change requires long-term strategies and on-going actions. Taking a poststructural perspective, it makes concrete suggestions to adapt and alter the Anti-Bias approach and the implementation of Anti-Bias trainings.

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Every German consumes per year, 15% is salmon, which is the third most popular fish in Germany after Alaska-Seelachs and Hering (Keller/Kress 2013: 9). But where does the salmon that ends up on our plates every 6th time we eat fish come from? There's no obligation for producers to declare the origin of their fish products, but if they do so, the latin name of the fish, catching method and catch area should be declared. Salmon, of which about 40% are captured in the wild and the rest brought up in aquacultures, could then be declared as follows: Salmon (salmo salar), aquaculture from Chile. Without any doubt, this makes consumption more transparent, but the standards of production – both, social and ecological ones – and the ecological impacts are still kept in the dark.

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This paper is an attempt to map the global land acquisitions with a focus on Indian MNCs in acquiring overseas land for agricultural purposes. It tries to outline the contemporary political economy of capital accumulation at the global level, especially, in the emerging developing economies like India and China, where the emergence of a new capitalist class has engaged itself into acquisition of land and control of other natural resources in Africa, Latin America, Eastern Europe and South East Asia, for example, water and other minerals to secure itself from the eventual losses of ongoing economic crisis and to earn profit from the volatile agricultural commodity markets. This sway of control of resources by the MNCs has got paramount State support under the helm of neoliberal policies. The paper provides scale of overseas land acquisitions at the current juncture and tries to highlight its causes and the major implications associated with it.

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Sketches are commonly used in the early stages of design. Our previous system allows users to sketch mechanical systems that the computer interprets. However, some parts of the mechanical system might be too hard or too complicated to express in the sketch. Adding speech recognition to create a multimodal system would move us toward our goal of creating a more natural user interface. This thesis examines the relationship between the verbal and sketch input, particularly how to segment and align the two inputs. Toward this end, subjects were recorded while they sketched and talked. These recordings were transcribed, and a set of rules to perform segmentation and alignment was created. These rules represent the knowledge that the computer needs to perform segmentation and alignment. The rules successfully interpreted the 24 data sets that they were given.

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We present an unsupervised learning algorithm that acquires a natural-language lexicon from raw speech. The algorithm is based on the optimal encoding of symbol sequences in an MDL framework, and uses a hierarchical representation of language that overcomes many of the problems that have stymied previous grammar-induction procedures. The forward mapping from symbol sequences to the speech stream is modeled using features based on articulatory gestures. We present results on the acquisition of lexicons and language models from raw speech, text, and phonetic transcripts, and demonstrate that our algorithm compares very favorably to other reported results with respect to segmentation performance and statistical efficiency.

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We present MikeTalk, a text-to-audiovisual speech synthesizer which converts input text into an audiovisual speech stream. MikeTalk is built using visemes, which are a small set of images spanning a large range of mouth shapes. The visemes are acquired from a recorded visual corpus of a human subject which is specifically designed to elicit one instantiation of each viseme. Using optical flow methods, correspondence from every viseme to every other viseme is computed automatically. By morphing along this correspondence, a smooth transition between viseme images may be generated. A complete visual utterance is constructed by concatenating viseme transitions. Finally, phoneme and timing information extracted from a text-to-speech synthesizer is exploited to determine which viseme transitions to use, and the rate at which the morphing process should occur. In this manner, we are able to synchronize the visual speech stream with the audio speech stream, and hence give the impression of a photorealistic talking face.

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abstract With many visual speech animation techniques now available, there is a clear need for systematic perceptual evaluation schemes. We describe here our scheme and its application to a new video-realistic (potentially indistinguishable from real recorded video) visual-speech animation system, called Mary 101. Two types of experiments were performed: a) distinguishing visually between real and synthetic image- sequences of the same utterances, ("Turing tests") and b) gauging visual speech recognition by comparing lip-reading performance of the real and synthetic image-sequences of the same utterances ("Intelligibility tests"). Subjects that were presented randomly with either real or synthetic image-sequences could not tell the synthetic from the real sequences above chance level. The same subjects when asked to lip-read the utterances from the same image-sequences recognized speech from real image-sequences significantly better than from synthetic ones. However, performance for both, real and synthetic, were at levels suggested in the literature on lip-reading. We conclude from the two experiments that the animation of Mary 101 is adequate for providing a percept of a talking head. However, additional effort is required to improve the animation for lip-reading purposes like rehabilitation and language learning. In addition, these two tasks could be considered as explicit and implicit perceptual discrimination tasks. In the explicit task (a), each stimulus is classified directly as a synthetic or real image-sequence by detecting a possible difference between the synthetic and the real image-sequences. The implicit perceptual discrimination task (b) consists of a comparison between visual recognition of speech of real and synthetic image-sequences. Our results suggest that implicit perceptual discrimination is a more sensitive method for discrimination between synthetic and real image-sequences than explicit perceptual discrimination.