Course contents: Main characteristics of the speech signal. Speech production models. Acoustic perception of speech and sound. Techniques and tools for digital processing of the speech signal. Linear prediction in speech processing, harmonic models and typical coding methods of the speech signal. Speech synthesis and Text-to-Speech systems. Speech recognition. Algorithm deployment in software platforms (e.g. MatLab).

Assessment: Written exams at the end of the semester which will contribute 50% to the final grade. Laboratory reports and/or oral examination and/or semester project presentation which will contribute 50% to the final grade. The aforementioned percentages may vary by ±10% depending on the requirements of the laboratory work each academic year.