Machine Learning for Speech and Language Technology (SIGML)

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Aims. The goal of the group is promoting research in modern machine learning specifically applied to speech and language processing, and of encouraging interaction between the speech community and the machine learning community. The group is also affiliated to the Association for Computational Linguistics and the International Machine Learning Society.

Motivation. Machine learning is one of the basic tools in speech and language processing.  In recent years, we see the migration of many novel techniques in machine learning to speech and language processing, such as boosting, large margin training, SVMs, deep neural nets to name a few.   At the same time, some techniques in machine learning have their origin in speech and language processing problems.  Nevertheless, speech research has historically enjoyed somewhat less interaction with machine learning than have other application areas (e.g., computer vision, natural language processing). Therefore, the main goal of this SIG will be to increase interaction between the speech and machine learning research communities.

Board. Current SIG officers are:

• Chairperson: Anton Ragni, U. of Sheffield, UK
  Secretary: Yao Qian, Microsoft Research, USA  & Hao Tang, MIT, USA
  ISCA liaison officer: Preethi Jyothi, IIT Bombay, India

ISCA-supported events

• Symposium on Machine Learning in Speech and Language Processing (MLSLP)
  • MLSLP 2018 (7/9, colocated with Interspeech 2018, Hyderabad, India) (proceedings)
  • MLSLP 2017 (11/8, colocated with ICML 2017, Sydney, Australia) (proceedings)
  • MLSLP 2016 (13/9, colocated with Interspeech 2016, San Francisco, CA, USA)
  • MLSLP 2012 (14/9, colocated with Interspeech 2012, Portland, OR, USA)
  • MLSLP 2011 (27/6, colocated with ICML 2011, Bellevue, Washington, USA)

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