NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Pérez Castillejo, Susana – Research-publishing.net, 2021
Automatic Speech Recognition (ASR) is a digital communication method that transforms spoken discourse into written text. This rapidly evolving technology is used in email, text messaging, or live video captioning. Current ASR systems operate in conjunction with Natural Language Processing (NLP) technology to transform speech into text that people…
Descriptors: Automation, Assistive Technology, Educational Technology, Speech Communication
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Bermudez-Gonzalez, Daniel; Miranda-Jiménez, Sabino; García-Moreno, Raúl-Ulises; Calderón-Nepamuceno, Dora – Research-publishing.net, 2016
Nowadays, machine learning techniques are being used in several Natural Language Processing (NLP) tasks such as Opinion Mining (OM). OM is used to analyse and determine the affective orientation of texts. Usually, OM approaches use affective dictionaries in order to conduct sentiment analysis. These lexicons are labeled manually with affective…
Descriptors: Dictionaries, Spanish, Natural Language Processing, Psychological Patterns
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Pareja-Lora, Antonio – Research-publishing.net, 2016
For the new approaches to language e-learning (e.g. language blended learning, language autonomous learning or mobile-assisted language learning) to succeed, some automatic functions for error correction (for instance, in exercises) will have to be included in the long run in the corresponding environments and/or applications. A possible way to…
Descriptors: Electronic Learning, Automation, Error Correction, Natural Language Processing
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Garnier, Marie – Research-publishing.net, 2012
According to recent studies, there is a persistence of adverb placement errors in the written productions of francophone learners and users of English at an intermediate to advanced level. In this paper, we present strategies for the automatic detection and correction of errors in the placement of manner adverbs, using linguistic-based natural…
Descriptors: Form Classes (Languages), Error Correction, Natural Language Processing, Feedback (Response)