Wady i ograniczenia systemów rozpoznawania mowy

• Autorzy: Karolina Kuligowska , Paweł Kisielewicz , Aleksandra Włodarz

Warianty tytułu

Speech Recognition Systems: Disadvantages and Limitations

• Języki publikacji: PL

Abstrakty

Rozpoznawanie mowy (ang. speech recognition, speech-to-text - STT) jest procesem umożliwiającym przekształcenie wypowiedzianych słów i zdań na tekst w postaci cyfrowej. Zaprojektowanie maszyny, która naśladuje zdolność człowieka do słuchania, fascynowało badaczy od stuleci. Jednakże dopiero w ciągu ostatniej dekady dziedzina technologii rozpoznawania mowy dynamicznie się rozwinęła, a obecnie budowane zaawansowane systemy potrafią reagować na spontaniczną mowę w języku naturalnym.(fragment tekstu)

EN

Speech is one of the easiest ways allowing communication between people and machines. Speech recognition technology makes everyday life easier: it is widely used in mobile phones, computers, tablets, cars, etc. However, the quality of automatic speech recognition is affected by many factors, therefore, so much effort is put into improving the performance of speech recognition systems. The aim of this paper is to present the current state of development of speech recognition systems and to examine their drawbacks and limitations. The paper discusses the current classification, construction and functioning of speech recognition systems, which gives an insight into the speech-to-text software implemented so far. The analysis of disadvantages and limitations of speech recognition systems has allowed identifying the weak points of these systems. Problems that are to be solved in the near future indicate the direction of further development of speech recognition systems.(original abstract)

Słowa kluczowe

PL

Nowe technologie; Systemy z bazą wiedzy; System rozpoznawania mowy

EN

High-tech; Knowledge based systems; Speech recognition system

• Czasopismo: Roczniki Kolegium Analiz Ekonomicznych / Szkoła Główna Handlowa
• Rocznik: 2018
• Numer: nr 49 Społeczno-ekonomiczne aspekty rozwoju gospodarki cyfrowej : koncepcje zarządzania i bezpieczeństwa
• Strony: 307--317

Twórcy

autor

Karolina Kuligowska

• Uniwersytet Warszawski

autor

Paweł Kisielewicz

• Profeosoft, Kraków

autor

Aleksandra Włodarz

• Profeosoft, Kraków

Bibliografia

• Benzeghiba M., De Mori R., Deroo O., Dupont S. i in., Automatic speech recognition and speech variability: A review, "Speech Communication" 2007, no. 49, s. 767-768.
• Biadsy F., Automatic Dialect and Accent Recognition and its Application to SpeechRecognition, rozprawa doktorska, Department of Computer Science, Columbia University, 2011, s. 1-2.
• Buttermore R., Lee-Perkins N., Developments in voice recognition technology, 13th Annual Freshman Engineering Conference, 2013, s. 3-4.
• Desai N., Dhameliya K., Desai V., Feature Extraction and Classification Techniques for Speech Recognition: A Review, "International Journal of Emerging Technology and Advanced Engineering" 2013, vol. 3, issue 12, s. 368.
• Gaikwad S., Gawali B., Yannawar P., A review on Speech Recognition Technique, "International Journal of Computer Applications" 2010, vol. 10, no. 3, s. 22.
• Gruhn R. E., Minker W., Nakamura S., Statistical Pronunciation Modeling for Non-Native Speech Processing, Signals and Communication Technology, Springer-Verlag,Berlin Heidelberg 2011, s. 13.
• Machida K., Ito A., Speech recognition under noisy environments using multiple microphones based on asynchronous and intermittent measurements, Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2013, s. 2.
• Mary L., Extraction and Representation of Prosody for Speaker, Speech and Language Recognition, SpringerBriefs in Electrical and Computer Engineering, Springer,2012, s. 17-19.
• Nouza J., Zdansky J., Cerva P., Silovsky J., Challenges in Speech Processing of Slavic Languages (Case Studies in Speech Recognition of Czech and Slovak), w: Development of Multimodal Interfaces: Active Listening and Synchrony, A. Esposito, N. Campbell, C. Vogel i in. (red.), Springer-Verlag, Berlin Heidelberg 2010, s. 227-229.
• Renals S., Hain T., Speech recognition, w: The Handbook of Computional Linguistics and Natural Language Processing, A. Clark, Ch. Fox, S. Lappin (red.), Wiley-Blackwell, 2010, s. 299-301.
• Saraswathi S., Geetha T. V., Design of language models at various phases of Tamil speech recognition system, "International Journal of Engineering, Science and Technology"2010, vol. 2, no. 5, s. 244-245.
• Shanthi T., Chelpa L., Review of Feature Extraction Techniques in Automatic Speech Recognition, "International Journal of Scientific Engineering and Technology"2013, vol. 2, issue 6, s. 483.
• Tarasiuk M., Gosiewski Z., Segmentacja mowy polskiej z wykorzystaniem transformacji falkowej, "Acta Mechanica et Automatica" 2010, vol. 4, no. 1, s. 92.
• Vrinda, Shekhar Ch., Speech recognition system for English language, "International Journal of Advanced Research in Computer and Communication Engineering"2013, vol. 2, issue 1, s. 919.
• Wu C.-H., Liu C.-H., Robust Speech Recognition for Adverse Environments, w: Modern Speech Recognition Approaches with Case Studies, S. Ramakrishnan (red.), Intech 2012, s. 3.
• Ziółko B., Ziółko M., Przetwarzanie mowy, Wydawnictwa AGH, Kraków 2011, s. 224-225.