Alexander Kain (kaina@ohsu.edu)

Center for Spoken Language Understanding (CSLU)
Institute on Development & Disability (IDD)
School of Medicine (SOM)
Oregon Health & Science University (OHSU)

ORCID 0000-0001-5807-9311



Research Support




CS 506/606 - Research Programming

Credits: 1
This course will cover important software for quantitative research. The first unit will focus on the UNIX programming environment with a special emphasis on version control. The second unit will cover the Python programming language, focusing on libraries for efficient numeric computation.

CS 506/606 - Speech Signal Processing

Credits: 3
Speech systems are becoming more and more commonplace in today's computer systems. Examples are speech recognition systems and Text-to-Speech synthesis systems. This course will introduce the fundamentals of the underlying speech signal processing that enables such systems. Topics include speech production and perception by humans, frequency transforms, filters, linear predictive features, pitch estimation, speech coding, speech enhancement, and prosodic speech modification.

CS 553/653 - Speech Synthesis

Credits: 3
This course will introduce students to the problem of synthesizing speech from text input. Speech synthesis is a challenging area that draws on expertise from a diverse set of scientific fields, including signal processing, linguistics, psychology, statistics, and artificial intelligence. Fundamental advances in each of these areas will be needed to achieve truly human-like synthesis quality and advances in other realms of speech technology (like speech recognition, speech coding, speech enhancement). In this course, we will consider current approaches to sub-problems such as text analysis, pronunciation, linguistic analysis of prosody, and generation of the speech waveform. Lectures, demonstrations, and readings of relevant literature in the area will be supplemented by student lab exercises using hands-on tools.

CS 506/606 - Computational Approaches to Speech and Language Disorders

Credits: 3
This course covers a range of speech and language analysis algorithms that have been developed for measurement of speech or language based markers of neurological disorders, for the creation of assistive devices, and for remedial applications. Topics will include introduction to speech and language disorders, robust speech signal processing, statistical approaches to pitch and timing modeling, voice transformation algorithms, speech segmentation, and modeling of disfluency. The class will use a wide array of clinical data, and will be closely tied to several ongoing research projects.

Peer-reviewed Publications


Text-to-Speech Synthesis (TTS)

Voice Conversion




Technical Reports

Audio Demos