Viseme

About: Viseme is a research topic. Over the lifetime, 865 publications have been published within this topic receiving 17889 citations.

Basic research in speech and lateralization of language: Some implications for reading disability

Abstract: Basic research in speech and the lateralization of language is shown to illuminate the problems of reading and some of its disabilities. First, it is pointed out how speech, or language for the ear, differs markedly from reading, or language for the eye. Though the sounds of speech are a very complex code and the optical shapes of written language are a simple cipher or alphabet on the phonemes, we all perceive speech easily but read only with difficulty. Perceiving speech is easy because, as members of the human race, we all have access to a special physiological apparatus that decodes the complex speech signal and recovers the segmentation of the linguistic message. Reading is hard because the phonemic segmentation, which is automatic and intuitive in the case of speech, must be made fully conscious and explicit. The syllabic method supplemented by phonics (used with certain reservations) is suggested for remediation of segmentation problems. Second, it is posited that since the sounds of speech are processed differently from non-speech sounds, the two should not be diagnosed and remediated interchangeably. Third, it is shown that the relationships among cerebral lateralization for language, handedness and poor reading can now be studied more meaningfully because of the recent development of new techniques. A truism often heard in the opening lecture of graduate classes in education is that we have few answers to the problems that beset us, only questions. In the field of reading, the difficulty may be owing at least in part to our impatient attempts to find immediate solutions for the teacher and the student in the classroom, and our consequent neglect of basic research. I should like to suggest today how knowledge of basic research in related disciplines may lead to clues for improving beginning reading instruction and the lot of the disabled reader—if only by affording us a deeper understanding of the reading process.

Prosody and speech recognition

Abstract: The best ebooks about Prosody And Speech Recognition that you can get for free here by download this Prosody And Speech Recognition and save to your desktop. This ebooks is under topic such as prosody dependent speech recognition on radio news book reviews: prosody and speech recognition aclweb prosody modeling for automatic speech recognition and prosodic and accentual information for automatic speech modeling the prosody of hidden events for improved word prosody modeling for automatic speech understanding: an prosody in speech recognition ida which words are hard to recognize? prosodic, lexical, and prosody recognition in male infant-directed speech prosody-enriched lattices for improved syllable recognition using prosody for the improvement of automatic speech prosody as a conditioning variable in speech recognition prosody dependent speech recognition with explicit using prosody to improve automatic speech recognition prosody for mandarin speech recognition: a comparative use of prosodic features for speech recognition a prosody-only decision-tree model for disfluency detection recognition of prosodic factors and detection of landmarks towards using prosody in speech recognition/understanding prosodic parsing for swedish speech recognition prosody dependent speech recognition with explicit direct modeling of prosody: an overview of applications in recognition and understanding of prosody speech recognition university of maryland modeling prosodic dynamics for speaker recognition cnbc automatic detection of prosody phrase boundaries for text predicting automatic speech recognition performance using two methods for assessing oral reading prosody prosody unsupervised adaptation sail asa speech prosody pal aging and speech prosody illinois speech and language a study on prosody analysis ijcer prosody modeling in concept-to-speech generation the contributions of prosody and semantic context in how prosody improves word recognition modeling and recognition of phonetic and prosodic factors using prosody to improve mandarin automatic speech recognition implications of prosody modeling for prosody recognition the limits of speech recognition university of maryland prosody and focus in speech to infants and adults the prosody-voice screening profile (pvsp): psychometric applications 5: speech recognition theme 1 speech importance of prosodic features in language identification a factored language model for prosody dependent speech modeling and recognition of phonetic and prosodic factors improvement of speech summarization using prosodic information

Neural Face Models for Example-Based Visual Speech Synthesis

Abstract: Creating realistic animations of human faces with computer graphic models is still a challenging task. It is often solved either with tedious manual work or motion capture based techniques that require specialised and costly hardware. Example based animation approaches circumvent these problems by re-using captured data of real people. This data is split into short motion samples that can be looped or concatenated in order to create novel motion sequences. The obvious advantages of this approach are the simplicity of use and the high realism, since the data exhibits only real deformations. Rather than tuning weights of a complex face rig, the animation task is performed on a higher level by arranging typical motion samples in a way such that the desired facial performance is achieved. Two difficulties with example based approaches, however, are high memory requirements as well as the creation of artefact-free and realistic transitions between motion samples. We solve these problems by combining the realism and simplicity of example-based animations with the advantages of neural face models. Our neural face model is capable of synthesising high quality 3D face geometry and texture according to a compact latent parameter vector. This latent representation reduces memory requirements by a factor of 100 and helps creating seamless transitions between concatenated motion samples. In this paper, we present a marker-less approach for facial motion capture based on multi-view video. Based on the captured data, we learn a neural representation of facial expressions, which is used to seamlessly concatenate facial performances during the animation procedure. We demonstrate the effectiveness of our approach by synthesising mouthings for Swiss-German sign language based on viseme query sequences.