Speech Synthesis Research Scientist - Parametric Text-to-Speech, HMMs, HSMMs, Glottal Source Modeling, MLLR, MAP, HTK, HTS, Festival, C++, Python, Java, Matlab, Machine Learning, Vocoding, Hidden Markov Models, Speech Signal Processing - Pasadena, CA
This position is concerned with research and development in statistical parametric speech synthesis. The work will have a particular focus on the development of structured acoustic models which take account of factors such as accent and speaking style, and on the development of machine learning techniques for vocoding. You will have a PhD in speech processing, computer science, cognitive science, linguistics, engineering, mathematics, or a related discipline. You will have the necessary programming ability to conduct research in this area, a background in statistical modeling using Hidden Markov Models, speech signal processing, and research experience in speech synthesis.
A background in one or more of the following areas is also desirable: statistical parametric text-to-speech synthesis using HMMs and HSMMs; glottal source modelling; speech signal modelling; speaker adaptation using the MLLR or MAP family of techniques; familiarity with software tools including HTK, HTS, Festival; and familiarity with modern machine learning.
- PhD (Prefered), M.Sc. in Computer Science or Electrical Engineering
- High proficiency in C++, Python, Java, Matlab
- Experience with data-driven statistical or machine learning methods
- Enjoys a highly collaborative environment with minimal supervision
- Experience with speech synthesis
Nice to have:
- Familiarity with linguistic phonetics
- Knowledge of basic digital signal processing techniques for audio
- Experience with software engineering best practices including unit testing, continuous integration, and source control