Braille Translation Software Free Download High Quality

English Braille is also known as the Grade-2 braille. It contains nearly 250 letters. Braille is not a language -- it is rather a script (alphabet) which can be used to write any language. Grade-1 braille goes letter-by-letter while transcribing a language. However, Grade-2 braille makes use of contractions in order to reduce the number of cells. Grade-3 braille is essentially a personal shorthand used by some people. It is never used in publications.

Unified English Braille (UEB) is a unified standard for English Braille. UEB was proposed to the Braille Authority of North America (BANA) in 1991. The need of UEB was felt because there were many specialized braille standards which conflicted with each in many ways. Such a scenario was threatening the braille-literacy as well as the viability of English braille itself.

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The braille script designed by Louis Braille uses tactile patterns made with six raised dots arranged in a 3 x 2 matrix, called the braille cell. One or more braille cells may represent a letter, number, punctuation or a symbol. The following table shows the Unicode Braille characters representing various braille cells.

As per the international convention, braille is always written in left-to-right direction. This convention is followed even for the languages that are written right-to-left. For example, Arabic is written right-to-left, but Arabic braille is written left-to-right.

Note 1: This braille translation tool and this page uses Unicode braille characters. Without a properly configured computer/mobile device, you may see question marks, boxes, or other symbols instead of braille characters. If that's the case with you, please contact your computer engineer.

Note 2: Please note that software cannot do a perfect braille translation. Many decisions regarding how to translate something into braille have to be taken by human translators. This is true especially in case of Grade 2 (contracted) braille. This braille translation tool attempts to achieve as much accuracy as possible through a program.

Duxbury Systems leads the world in software for braille. The Duxbury Braille Translator (DBT)is used by virtually all of the world's leading braille publishers. No one supports more languages than Duxbury Systems. DBT supportsover 180 languages in either uncontracted or contracted (when such rules exist) braille.Our software can produce contracted and uncontracted literary, mathematics, and technical braille.

NimPro prepares NIMAS documents (and all DAISY format documents) for braille translation by DBT, easing the production of textbooks and K-12 instructional materials, including MathML. NimPro 3.0 handles EPUB 3 documents as well.

Although people who are blind use speech output systems to read aloud electronic documents, tactile formats are often most effective in highly technical disciplines such as mathematics, physics, computer science, and engineering. Braille translation software translates electronic documents into braille code. From these files, a refreshable braille display can present tactile braille or a braille embosser can produce a hard-copy on special paper.

Commonly used products include Duxbury Braille Translator and Braille2000. Open source braille translation programs include KNFB Reader or LibLouis. Specific applications provide support for a wide array of electronic document formats that may include ASCII, RTF, MS Word, Word Perfect, PDF, HTML, and XML, as well as files prepared according to the NIMAS textbook or DAISY digital talking book standards. Some products also support math equation formats, such as LaTeX, MathType, or MathML.

For more information on this topic, consult the Knowledge Base articles What are some techniques for creating braille math materials?, What is a refreshable braille display?, and In a postsecondary setting, who is responsible for providing braille translation?

Liblouis is a free and open-source braille translation system that powers screen readers such as NVDA, JAWS to work with refreshable braille display in various languages, as well as a variety of conversion tools including the DAISY Pipeline. To facilitate accurate translation Liblouis has dedicated braille tables for each language that it supports.

If a language is supported by Liblouis, then it is possible to read create a braille version of a document in that language for use on a refreshable braille display such as an Orbit Reader, or embossed on braille paper.

Considering the importance of Liblouis in supporting braille usage on refreshable braille displays and for the production of braille books, the DAISY Consortium is seeking assistance in compiling a list of languages that are not yet supported in Liblouis and in which accessible books are currently published. We are also seeking feedback on languages that are currently supported, but in which the braille translation may not be correct.

Once we have identified these gaps we will be able to plan for filling them by adding braille tables of identified languages. If you are aware of any language in which accessible books are published and braille translation tables are not available or currently adequate please let us know:

You can see in the above image that SignAgent will automatically translate your messages into whatever braille languages you've set up. The example above has both a Grade 1 and Grade 2 language for contrast.

Any messages created or changed within signs will be automatically translated, but if you change a primary message in this table, you'll need to regenerate the translation by clicking on the refresh button to the right of the translated message.

When editing sign type fields, the translation version of the fields you entered in step 2.5 above will now be available. In this example, the system will automatically translate whatever is entered into the "Room Number" field into braille for the "Room Number US Braille Grade 2" field.

An important sign of the accessibility of Braille information is the mutual translation between Chinese and Braille so that no significant differences can be found between the original and translated Chinese characters on smart devices. Braille is a special script with the properties of the host. Braille generally does not exist independently (there is no Braille used in a country that can be separated from a certain language, and there is no Braille that is used internationally across languages), and there are both associations and differences with the host language. The appearance of Braille is the same all over the world, but the difference in the host language makes the Braille of the corresponding language completely different from others. The informatization of English Braille is easy to complete, and the level of informatization is also high, so that blind people who use English can be well educated, which helps to promote social equity and to achieve great social significance.

The above-mentioned irregularities and uncertainties hinder the translation of Chinese to Braille and make it difficult to improve the Braille informatization at a certain level. Researchers have been looking for breakthroughs for many years, but the results are not obvious. This is also the original intention of the nation to promulgate and promote the Chinese Common Braille.

The remainder of this paper is arranged as follows. In Section 2, we will introduce the detailed information of the Chinese-Braille word corpus provided by the team of Professor Jing-Hua Zhong of Beijing Union University as we carried out our research based on this dataset. We will present the detailed procedures of our developed system in Section 3, where we will firstly introduce the details of translation from Chinese to Braille and vice versa. We then proposed our method for Braille word segmentation and concatenation. Specifically, we firstly deploy the n-gram model to segment Chinese words and then train a Braille word segmentation concatenation dictionary to generate a unigram language model for Braille word segmentation adjustment. By doing so, we aimed at improving the translation accuracy from Chinese to Braille. Finally, we improved the Braille Word Segmentation and Concatenation Rules by experiment. The details of the experiment are presented in Section 5. In terms of translation from Chinese Common Braille in the field of educational literature, the accuracy has reached 95.01% while the translation accuracy reached 90.15% when translating Chinese Common Braille to Chinese.

The release of the Chinese Common Braille has fundamentally solved the problem of Braille marking. Therefore, in the translation process from Chinese to Braille, the core difficulty is the Braille Word Segmentation and Concatenation Rules [12].

In the translation process, there are also some details that need to be coped with. For example, according to the representation rules of the Chinese Common Braille, the comparison table between Chinese Pinyin and the Chinese Common Braille, numerous tables have to be made, such as the comparison table between the numerical symbols and the Chinese Common Braille, the comparison table between the English letters and the Chinese Common Braille, and the comparison table between various symbols and the Chinese Common Braille. When brailing various characters, firstly, it is necessary to solve the problem of adding prompt symbols when Chinese, English, various numbers, symbols, and other text symbols are mixed; secondly, it is necessary to solve various noncontent symbols (such as hyphens), format prompts, etc.

The Chinese-Braille translation is just the direct translation from Chinese characters into Braille. The sentence can contain non-Chinese characters such as numbers, English, and punctuation marks, but there is a one-to-one correspondence between such information and Braille, where direct conversion can be applied. The accuracy, however, is very high already and will not be discussed here.

The biggest technical problem in Chinese-Braille translation is the Braille Word Segmentation and Concatenation Rules. With the simultaneous development of machine translation technology, Chinese word segmentation technology methods are divided into rule-based, statistical-based, and deep learning [16]. The rule-based method mainly depends on the dictionary, and the more classic ones are the maximum matching. The advantage is that it is simple, easy, and efficient; the disadvantage is that it depends on the accuracy and scale of the dictionary, and the recognition ability of ambiguous words is poor. The statistical methods rely on the corpus and use the corpus context information, word frequency, information entropy, etc., to perform word segmentation. The more classic ones are based on n-gram, maximum entropy model, hidden Markov model (HMMs) [17], conditional random field model (CRF), and so on. The advantage is that the accuracy rate is significantly improved, and the disadvantage is that it relies on a relatively large-scale corpus, which causes bias problems (maximum entropy model, hidden Markov model) or model complexity and low efficiency (CRF). The N-shortest tokenizer has a better effect than the shortest tokenizer and has a stronger ability to recognize named entities, but the speed is much slower; the CRF (conditional random field) methods usually have an accuracy and recall rate that are higher than 96% and have good new word recognition ability. In recent years, neural networks and deep learning methods are very eye-catching techniques [18]. Deep learning has made outstanding achievements in natural language processing, image recognition (especially medical image recognition [19, 20]), target detection, and so on. Deep learning includes Convolutional Neural Networks (CNNs) to Recurrent Neural Networks (RNNs) to long- and short-term memory neural network model LSTM [21] and improved variations of LSTM. The advantage is that the effect is good, and the disadvantage is that it relies on a large-scale corpus, long training time, and poor interpretability. Of course, there is also a combination of the above-mentioned methods to achieve good results and high efficiency as much as possible. ff782bc1db