Speech Recognition: Transcription and transformation of human speech
Abstract
The specified subfield of computational linguistics and computer science can said to be linked with speech recognition. Speech recognition can develop new variation technologies as well as methodologies generated as interdisciplinary concept. It can be considered to translate and recognize and satisfy the capability towards understanding and translating the words that are already spoken. It is more preciously said that in the most recent times this field has secured positive feedback by intense learning of voice recognition. Such evidences shows the proof that it has more market demand for implementing the application of specific data as voice recognition. Deployment of speech recognition systems can be utilized as the evidence shown to its analyzing methods that is helpful for designing each and every individual’s future. It is said that the computer plays an important role for this process as by this all the translated words can be acknowledged by the texts also.
References
Barker, J., Watanabe, S., Vincent, E. and Trmal, J., 2018. The fifth'CHiME'speech separation and recognition challenge: dataset, task and baselines. arXiv preprint arXiv:1803.10609.
Fontan, L., Ferrané, I., Farinas, J., Pinquier, J., Tardieu, J., Magnen, C., Gaillard, P., Aumont, X. and Füllgrabe, C., 2017. Automatic speech recognition predicts speech intelligibility and comprehension for listeners with simulated age-related hearing loss. Journal of Speech, Language, and Hearing Research, 60(9), pp.2394-2405.
Greibus, M., Ringelienė, Ž. and Telksnys, L., 2017, April. The phoneme set influence for Lithuanian speech commands recognition accuracy. In 2017 Open Conference of Electrical, Electronic and Information Sciences (eStream) (pp. 1-4). IEEE.
Guglani, J. and Mishra, A.N., 2018. Continuous Punjabi speech recognition model based on Kaldi ASR toolkit. International Journal of Speech Technology, 21(2), pp.211-216.
Helmke, H., Slotty, M., Poiger, M., Herrer, D.F., Ohneiser, O., Vink, N., Cerna, A., Hartikainen, P., Josefsson, B., Langr, D. and Lasheras, R.G., 2018, September. Ontology for transcription of ATC speech commands of SESAR 2020 solution PJ. 16-04. In 2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC) (pp. 1-10). IEEE.
Hsu, W.N., Tang, H. and Glass, J., 2018. Unsupervised adaptation with interpretable disentangled representations for distant conversational speech recognition. arXiv preprint arXiv:1806.04872.
Hsu, W.N., Zhang, Y. and Glass, J., 2017, December. Unsupervised domain adaptation for robust speech recognition via variational autoencoder-based data augmentation. In 2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU) (pp. 16-23). IEEE.
Iter, D., Huang, J. and Jermann, M., 2017. Generating adversarial examples for speech recognition. Stanford Technical Report.
Lojka, M., Viszlay, P., Staš, J., Hládek, D. and Juhár, J., 2018, September. Slovak broadcast news speech recognition and transcription system. In International Conference on Network-Based Information Systems (pp. 385-394). Springer, Cham.
Salimbajevs, A. and Ikauniece, I., 2017. System for Speech Transcription and Post-Editing in Microsoft Word. In INTERSPEECH (pp. 825-826).
Schönherr, L., Kohls, K., Zeiler, S., Holz, T. and Kolossa, D., 2018. Adversarial attacks against automatic speech recognition systems via psychoacoustic hiding. arXiv preprint arXiv:1808.05665.
Tjandra, A., Sakti, S. and Nakamura, S., 2017, December. Listening while speaking: Speech chain by deep learning. In 2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU) (pp. 301-308). IEEE
In submitting the manuscript to the International Journal on Integrated Education (IJIE), the authors certify that:
- They are authorized by their co-authors to enter into these arrangements.
- The work described has not been formally published before, except in the form of an abstract or as part of a published lecture, review, thesis, or overlay journal.
- That it is not under consideration for publication elsewhere,
- The publication has been approved by the author(s) and by responsible authorities – tacitly or explicitly – of the institutes where the work has been carried out.
- They secure the right to reproduce any material that has already been published or copyrighted elsewhere.
- They agree to the following license and copyright agreement.
License and Copyright Agreement
Authors who publish with International Journal on Integrated Education (IJIE) agree to the following terms:
- Authors retain copyright and grant the International Journal on Integrated Education (IJIE) right of first publication with the work simultaneously licensed under Creative Commons Attribution License (CC BY 4.0) 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 International Journal on Integrated Education (IJIE) published version of the work (e.g., post it to an institutional repository or edit 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.