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Scanning speech is a type of ataxic dysarthria in which spoken words are broken up into separate syllables, often separated by a noticeable pause, and spoken with varying force. [1] The sentence "Walking is good exercise", for example, might be pronounced as "Walk (pause) ing is good ex (pause) er (pause) cise".
Reading is an area that has been extensively studied via the computational model system. The dual-route cascaded model (DRC) was developed to understand the dual-route to reading in humans. [14] Some commonalities between human reading and the DRC model are: [5] Frequently occurring words are read aloud faster than non-frequently occurring words.
Subvocalization, or silent speech, is the internal speech typically made when reading; it provides the sound of the word as it is read. [1] [2] This is a natural process when reading, and it helps the mind to access meanings to comprehend and remember what is read, potentially reducing cognitive load.
Speech processing is the study of speech signals and the processing methods of signals. The signals are usually processed in a digital representation, so speech processing can be regarded as a special case of digital signal processing, applied to speech signals. Aspects of speech processing includes the acquisition, manipulation, storage ...
In speech communication, intelligibility is a measure of how comprehensible speech is in given conditions. Intelligibility is affected by the level (loud but not too loud) and quality of the speech signal, the type and level of background noise, reverberation (some reflections but not too many), and, for speech over communication devices, the properties of the communication system.
Reading is the process of taking in the sense or meaning of symbols, often specifically those of a written language, by means of sight or touch. [1] [2] [3] [4]For educators and researchers, reading is a multifaceted process involving such areas as word recognition, orthography (spelling), alphabetics, phonics, phonemic awareness, vocabulary, comprehension, fluency, and motivation.
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Deep learning speech synthesis refers to the application of deep learning models to generate natural-sounding human speech from written text (text-to-speech) or spectrum . Deep neural networks are trained using large amounts of recorded speech and, in the case of a text-to-speech system, the associated labels and/or input text.