Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Design and Analysis of an Intelligent Speech Recognition System

Author : Baibaswata Mohapatra 1 Akanksha Sehgal 2

Date of Publication :20th September 2017

Abstract: It is critical to recognize speech acknowledgment from speech comprehension (or speech distinguishing proof), the importance of an expression instead of its translation. Speech acknowledgment is likewise not the same as voice acknowledgment: though speech acknowledgment alludes to the capacity of a machine to perceive the words that are verbally expressed (i.e., what is said), voice acknowledgment includes the capacity of a machine to perceive talking style (i.e., who said something). The proposed research work is a savvy speech acknowledgment framework and it depends on Deep learning. The utilization of voice as a characteristic and supportive method for human-device correspondence is prevalently identified with sans hands things and correspondence with little structure factor gadgets. This new territory of AI has yielded far superior outcomes when contrasted with others in an assortment of utilizations including speech, and along these lines turned into an alluring zone of research. It is worked for train the framework the continuous condition and perform better at both raucous and raucous free condition having individuals of various talking styles and talking rate.

Reference :

    1. S. Toshniwal et al., “Multilingual Speech Recognition with a Single End-to-End Model,” in ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 2018, doi: 10.1109/ICASSP.2018.8461972.
    2. T. Schultz and K. Kirchhoff, Multilingual Speech Processing. 2006.
    3. J. B. Mariño, A. Moreno, and A. Nogueiras, “A first experience on multilingual acoustic modeling of the languages spoken in Morocco,” in 8th International Conference on Spoken Language Processing, ICSLP 2004, 2004.
    4. R. Dufour, Y. Estève, and P. Deléglise, “Characterizing and detecting spontaneous speech: Application to speaker role recognition,” Speech Commun., 2014, doi: 10.1016/j.specom.2013.07.007.
    5. N. T. Vu, Y. Wang, M. Klose, Z. Mihaylova, and T. Schultz, “Improving SSR performance on non-native speech using multilingual and crosslingual information,” in Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, 2014.
    6. S. Watanabe, T. Hori, and J. R. Hershey, “Language independent end-to-end architecture for joint language identification and speech recognition,” in 2017 IEEE Automatic Speech Recognition and Understanding Workshop, SSRU 2017 - Proceedings, 2018, doi: 10.1109/SSRU.2017.8268945.
    7. H. Tang, W. Liu, W. L. Zheng, and B. L. Lu, “Multimodal Emotion Recognition Using Deep Neural Networks,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, doi: 10.1007/978-3- 319-70093-9_86.
    8. W. Song and J. Cai, “End-to-End Deep Neural Network for Automatic Speech Recognition,” CS224N Proj., 2015.
    9. A. B. Nassif, I. Shahin, I. Attili, M. Azzeh, and K. Shaalan, “Speech Recognition Using Deep Neural Networks: A Systematic Review,” IEEE Access, vol. 7, pp. 19143– 19165, 2019, doi: 10.1109/ACCESS.2019.2896880.
    10. Samudravijaya K, “Automatic Speech Recognition.”
    11. J. PECKHAM, “AUTOMATIC SPEECH

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