A Speech to Text Transcription Approach based on Romanian Corpus

Authors

  • Andrei Scutelnicu Alexandru Ioan Cuza University of Iasi, Institute of Computer Science, Romanian Academy, Iasi
  • Mihaela Onofrei Alexandru Ioan Cuza University of Iasi, Institute of Computer Science, Romanian Academy, Iasi
  • Anca Diana Bibiri Alexandru Ioan Cuza University of Iasi
  • Mircea Hulea Gheorghe Asachi University of Iasi

Keywords:

speech recognition, formant energy, algorithmic method, neural network

Abstract

Automatic speech segmentation has many applications in speech processing and phonetics, e.g., in automatic speech recognition and automatic annotation of speech corpora. In both processes of training and evaluation of speech recognition systems large aligned speech-to-text corpora are needed. Once aligned, identification of phonemes could be based on samples that are picked-up inbetween phonemes’ boundaries. Because manual segmentation is costly and extremely time consuming, automatic methods of alignment are searched for. In this paper, we propose a simple, yet efficient, method for speech to text recognition based on a machine learning approach, using a Romanian speech corpus.

Author Biographies

Anca Diana Bibiri, Alexandru Ioan Cuza University of Iasi

Anca Diana Bibiri

Alexandru Ioan Cuza University of Iasi, Romania Bulevardul Carol I 11, Ia?i 700506, Tel. +40 232 201 000 anca.bibiri@gmail.com

Mircea Hulea, Gheorghe Asachi University of Iasi

Mircea Hulea

Faculty of Automatic Control and Computer Engineering, Gheorghe Asachi University of Ia?i, Romania, 67 Bulevardul Profesor Dimitrie Mangeron, Ia?i 700050, Tel. +40 232 278 683 mhulea@tuiasi.ro

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Published

2017-12-23

How to Cite

Scutelnicu, A., Onofrei, M., Bibiri, A. D., & Hulea, M. (2017). A Speech to Text Transcription Approach based on Romanian Corpus. BRAIN. Broad Research in Artificial Intelligence and Neuroscience, 8(4), pp. 17-24. Retrieved from https://lumenpublishing.com/journals/index.php/brain/article/view/2099

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