Speech technologies

Speech technologies

1.

Subject title

Speech technologies

Говорни технологии

2.

Code

m23_w_068

3.

Study program

Cloud Computing, IT management, Bioinformatics, Security, Cryptography and Coding, Еducation with ICT, Eco-informatics, Inteligent Systems, Internet Technologies and cyber security, Computer Science, Statistics and Data Analytics, Software for embedded systems, Software Engineering, Cloud Computing, IT management, Bioinformatics, Security, Cryptography and Coding, Statistics and Data Analytics, Software Engineering, Data science in computer science and engineering,

4.

Organizer of the study program (unit, institute, department, division)

Faculty of Information Sciences and Computer Engineering

5.

Study cycle (first, second, third)

Втор циклус

6.

Academic year / semester

5 / Зимски

7. Number of ECTS credits

6.0

8.

Instructor

ворн. проф. д-р Моника Симјаноска Мишева

9.

Prerequisites for enrollment

10.

Subject goals and competencies:


Introduction to spoken language technology with an emphasis on dialog and conversational systems. Deep learning and other methods for automatic speech recognition, speech synthesis, affect detection, dialogue management, and applications to digital assistants and spoken language understanding systems.

11.

Subject content:


Introduction and Acoustic Phonetics. Introduction to Dialog. Machine Learning in Dialog. Course Project & Automatic Speech Recognition (ASR) Introduction. Automatic Speech Recognition. Advanced ASR. Spoken language products with modern toolkits. Speech Synthesis / Text to Speech (TTS). Practical TTS and Meaning Extraction. Poster Presentations and Wrap-up.

12.

Learning methods:


Предавања поддржани со презентации преку слајдови, интерактивни предавања, вежби (користење на опрема и софтверски пакети), самостојна изработка и одбрана на проектна задача и семинарска работа, учење во електронско опкружување (форуми, консултации).

13.

Total available time fund

6.0 ECTS x 30 hours = 180 hours

14.

Time distribution

60 + 40 + 30 + 50 + 0 = 180 hours

15.

Forms of teaching activities

15.1.

Lectures - theoretical teaching

60 hours

15.2.

Exercises (laboratory, classroom), seminars, team work

40 hours

16.

Other forms of activities

16.1.

Project tasks

50 hours

16.2.

Independent tasks

30 hours

16.3.

Homework

0 hours

17.

Grading method

17.1.

Tests

0 points

17.2.

Seminar work / project (presentation: written and oral)

50 points

17.3.

Activities and learning

10 points

17.4.

Final exam

40 points

18.

Grading criteria (points / grade)

up to 50 points

5 (five) (F)

from 51 to 60 points

6 (six) (E)

from 61 to 70 points

7 (seven) (D)

from 71 to 80 points

8 (eight) (C)

from 81 to 90 points

9 (nine) (B)

from 91 to 100 points

10 (ten) (A)

19.

Condition for signature and taking final exam

NULL

20.

Language of instruction

Македонски и англиски

21.

Quality assurance method

Mеханизам на интерна евалуација и анкети

22.

Literature

22.1.

Mandatory literature

No.

Author

Title

Publisher

Year

7709

David J. Peterson

The Art of Language Invention

Penguin Books

2015

7710

Daniel Jurafsky & James H. Martin

Speech and Language Processing

Stanford University Press

2021

7711

Yue Zhang & Zhiyang Teng

Natural Language Processing: A Machine Learning Perspective

Cambridge University Press

2021

7712

Li Deng & ‎Yang Liu

Deep Learning in Natural Language Processing

Springer

2018

22.2.

Additional literature

No.

Author

Title

Publisher

Year