Browse all content tagged with Speech Recognition
Audio transcription is the process of converting spoken language from audio recordings into written text, making speeches, interviews, lectures, and other audio formats accessible and searchable. Advances in AI have improved transcription accuracy and efficiency, supporting media, academia, legal, and content creation industries.
A Corpus (plural: corpora) in AI refers to a large, structured set of texts or audio data used for training and evaluating AI models. Corpora are essential for teaching AI systems how to understand, interpret, and generate human language.
What is a Heteronym? A heteronym is a unique linguistic phenomenon where two or more words share the same spelling but have different pronunciations and meanings. These words are homographs that are not homophones. In simpler terms, heteronyms look identical in written form but sound different when spoken, and they convey distinct meanings based on context.
Hidden Markov Models (HMMs) are sophisticated statistical models for systems where underlying states are unobservable. Widely used in speech recognition, bioinformatics, and finance, HMMs interpret hidden processes and are powered by algorithms like Viterbi and Baum-Welch.
A neural network, or artificial neural network (ANN), is a computational model inspired by the human brain, essential in AI and machine learning for tasks like pattern recognition, decision-making, and deep learning applications.
Pattern recognition is a computational process for identifying patterns and regularities in data, crucial in fields like AI, computer science, psychology, and data analysis. It automates recognizing structures in speech, text, images, and abstract datasets, enabling intelligent systems and applications such as computer vision, speech recognition, OCR, and fraud detection.
Recurrent Neural Networks (RNNs) are a sophisticated class of artificial neural networks designed to process sequential data by utilizing memory of previous inputs. RNNs excel in tasks where the order of data is crucial, including NLP, speech recognition, and time-series forecasting.
Speech recognition, also known as automatic speech recognition (ASR) or speech-to-text, enables computers to interpret and convert spoken language into written text, powering applications from virtual assistants to accessibility tools and transforming human-machine interaction.
Speech recognition, also known as automatic speech recognition (ASR) or speech-to-text, is a technology that enables machines and programs to interpret and transcribe spoken language into written text. This powerful capability is distinct from voice recognition, which identifies an individual speaker’s voice. Speech recognition focuses purely on translating verbal speech into text.
OpenAI Whisper is an advanced automatic speech recognition (ASR) system that transcribes spoken language into text, supporting 99 languages, robust to accents and noise, and open-source for versatile AI applications.
