Our second example deals with a more challenging problem: the recognition of hand-printed letters of the alphabet. The characters that people print in the ordinary course of filling out forms and questionnaires are surprisingly varied. Gaps abound wherecontinuous lines might be expected; curves and sharp angles appear interchangeably; there is almost every imaginable distortion of slant, shape and size. Even human readers cannot always identify such characters; their error rate is about 3 per cent on randomly selected letters and numbers, seen out of context.
– from Oliver G. Selfridge & Ulric Neisser. PATTERN RECOGNITION BY MACHINE . In Computers & thought, Edward A. Feigenbaum and Julian Feldman (Eds.). MIT Press, Cambridge, MA, USA, 1963. pp. 8-30.
Optical character recognition (OCR) is a technology that allows computers to recognize and extract text from images, such as scanned documents, photographs, bills, etc. The process involves analyzing the image and identifying the individual characters within it and then converting those characters into machine-readable text. OCR software can be used to automate tasks such as document scanning, business automation, and accessibility technology. OCR software uses complex algorithms and pattern recognition techniques to identify and extract text. OCR technology has evolved over time and now it has the ability to recognize text in multiple languages and different fonts.
Last year saw the emergence of artificial intelligence tools (AI) that can create images, artwork, or even video with a text prompt. There were also major steps forward in AI writing, with OpenAI's ChatGPT causing widespread excitement - and fear - about the future of writing. Now just a few days into 2023, another powerful use case for AI has stepped into the limelight - a text-to-voice tool that can impeccably mimic a person's voice. Developed by Microsoft, VALL-E can take a three-second recording of someone's voice, and replicate that voice turning written words into speech, with realistic intonation and emotion depending on the context of the text. Trained with 60,000 hours worth of English speech recordings, it can deliver a speech in "zero-shot situation," which means without any prior examples or training in a specific context or situation.
Apple's website says the feature is initially only available for romance and fiction books, where it lists two available digital voices: Madison and Jackson. The service is only available in English at present, and Apple is oddly specific about the genres of books its digital narrators are able to tackle. "Primary category must be romance or fiction (literary, historical, and women's fiction are eligible; mysteries and thrillers, and science fiction and fantasy are not currently supported)," its website reads.
Text to speech is a process to convert any text into voice. Text to speech project takes words on digital devices and convert them into audio with a button click or finger touch. Text to speech python project is very helpful for people who are struggling with reading. To implement this project, we will use the basic concepts of Python, Tkinter, gTTS, and playsound libraries. The objective of this project is to convert the text into voice with the click of a button.
Some operations and tasks don't require painstaking attention to detail. With sensitive salary and wage information, bank and direct deposit accounts, social security numbers, and other personal information in play, the stakes are high. When preparing a payroll run or supporting payroll operations, it's important to follow a ...
Fox News correspondent Mike Tobin reports that severe weather disrupts travel plans ahead of the holidays on'Special Report.' FedEx and UPS announced mail delivery could be interrupted by the massive winter storm moving across the U.S. after key distribution hubs were blasted by the severe weather conditions. On Friday, FedEx posted a statement to its website warning those who used its Express service that the guaranteed delivery date of Dec. 26 may not be met after the Memphis and Indianapolis hubs experienced "substantial" weather disruptions. The shipping company said actions have been taken to lessen any impact on delivery, but the safety of its team members is the "number one priority." "We recognize the importance of deliveries this holiday weekend and are committed to providing service to the best of our ability by implementing contingency measures where it is safe and possible to do so," the statement read.
Handwriting Recognition has been a field of great interest in the Artificial Intelligence domain. Due to its broad use cases in real life, research has been conducted widely on it. Prominent work has been done in this field focusing mainly on Latin characters. However, the domain of Arabic handwritten character recognition is still relatively unexplored. The inherent cursive nature of the Arabic characters and variations in writing styles across individuals makes the task even more challenging. We identified some probable reasons behind this and proposed a lightweight Convolutional Neural Network-based architecture for recognizing Arabic characters and digits. The proposed pipeline consists of a total of 18 layers containing four layers each for convolution, pooling, batch normalization, dropout, and finally one Global average pooling and a Dense layer. Furthermore, we thoroughly investigated the different choices of hyperparameters such as the choice of the optimizer, kernel initializer, activation function, etc. Evaluating the proposed architecture on the publicly available 'Arabic Handwritten Character Dataset (AHCD)' and 'Modified Arabic handwritten digits Database (MadBase)' datasets, the proposed model respectively achieved an accuracy of 96.93% and 99.35% which is comparable to the state-of-the-art and makes it a suitable solution for real-life end-level applications.
A language model uses machine learning to conduct a probability distribution over words used to predict the most likely next word in a sentence based on the previous entry. Language models learn from text and can be used for producing original text, predicting the next word in a text, speech recognition, optical character recognition and handwriting recognition.
Countless human hours are required to manually extract the data into a machine-readable format. This process is known as ETL (extract, transform, and load). Insurers that can maximize their ETL capabilities have a powerful competitive advantage. Optical character recognition, also known as text recognition, converts text from scanned paper documents, photos, books, and PDF files into a machine-readable format, isn't new. What is new is coupling OCR with AI and machine-learning algorithms to reliably generate text that can be processed, indexed, and retrieved.
While there are all kinds of tips and tools to help you multitask, sometimes the best solutions are hiding in plain sight. A text-to-speech converter is one of those simple things that can help you listen to documents you have to read while working on something else, or add quality narration to videos and seminars to save you time from recording voices yourself. There are myriad applications, and Notevibes is one of the best solutions on the market.