A detailed survey of Turkish automatic speech recognition


Arslan R. S., BARIŞÇI N.

TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, cilt.28, sa.6, ss.3253-3269, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Derleme
  • Cilt numarası: 28 Sayı: 6
  • Basım Tarihi: 2020
  • Doi Numarası: 10.3906/elk-2001-38
  • Dergi Adı: TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, INSPEC, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.3253-3269
  • Anahtar Kelimeler: Turkish speech processing, automatic speech recognition (ASR), feature extraction, classifiers, end-point detection, robust ASR, LANGUAGE, OPTIMIZATION, ALGORITHM, MODEL
  • Gazi Üniversitesi Adresli: Evet

Özet

Significant improvements have been made in automatic speech recognition (ASR) systems in terms of both the general technology and the software used. Despite these advancements, however, there is still an important difference between the recognition performance of humans and machines. This work focuses on the studies conducted in the field of Turkish speech recognition, the progress made in such studies in recent years, the language-specific constraints, the performance results achieved in the applications developed to date, and the development of a general scheme for researchers wishing to develop an ASR system for the Turkish language. A comprehensive study on the Turkish language, including all literature and speech recognition systems, was prepared. There has been significant progress in the languages of developed countries in terms of ASR systems, but it was observed in this work that the opposite is true for the Turkish language. The lack of labor force and material resources remains the biggest obstacle to developing better systems. As a result, concrete studies are needed to achieve an ASR system with performance equivalent to the human level for the Turkish language.