Implementation of a Large Vocabulary Continuous Speech Recognition System for Brazilian Portuguese
Main Article Content
Abstract
This work presents the implementation of a large vocabulary speech recognition system for Brazilian Portuguese. The implemented system uses tools available on HTK and ATK toolkits. Tests were conducted in order to check the correlation on the context of continuous speech recognition among the following variables: word recognition rate, perplexity, distinct language models, computational complexity and vocabulary size. A speech database was used to train the stochastic acoustic models based on continuous HMMs, and a textual database was developed to train language models based on n-grams. Vocabularies ranging between 3.528 and 60.000 words were tested. The best accuracy rate obtained with a dictionary size of 3.528 words was 90% when recognizing sentences with 9 to 12 words, and 81% with 60.0000 words, both of them being speaker dependent, with perplexities ranging between 250 and 350, and processing times less than one minute per sentence.
Article Details
How to Cite
Teruszkin, R., & Gil Vianna Resende Junior, F. (2015). Implementation of a Large Vocabulary Continuous Speech Recognition System for Brazilian Portuguese. Journal of Communication and Information Systems, 21(3). https://doi.org/10.14209/jcis.2006.18
Issue
Section
Regular Papers
Authors who publish in this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors can enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) before and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
___________