Speech Recognition - Further Information

Further Information

Popular speech recognition conferences held each year or two include SpeechTEK and SpeechTEK Europe, ICASSP, Interspeech/Eurospeech, and the IEEE ASRU. Conferences in the field of natural language processing, such as ACL, NAACL, EMNLP, and HLT, are beginning to include papers on speech processing. Important journals include the IEEE Transactions on Speech and Audio Processing (now named IEEE Transactions on Audio, Speech and Language Processing), Computer Speech and Language, and Speech Communication. Books like "Fundamentals of Speech Recognition" by Lawrence Rabiner can be useful to acquire basic knowledge but may not be fully up to date (1993). Another good source can be "Statistical Methods for Speech Recognition" by Frederick Jelinek and "Spoken Language Processing (2001)" by Xuedong Huang etc. More up to date is "Computer Speech", by Manfred R. Schroeder, second edition published in 2004. The recently updated textbook of "Speech and Language Processing (2008)" by Jurafsky and Martin presents the basics and the state of the art for ASR. Speaker recognition also uses the same features, most of the same front-end processing, and classification techniuqes as is done in speech recognition. A most recent comprehensive textbook, "Fundamentals of Speaker Recognition" by Homayoon Beigi, is an in depth source for up to date details on the theory and practice. A good insight into the techniques used in the best modern systems can be gained by paying attention to government sponsored evaluations such as those organised by DARPA (the largest speech recognition-related project ongoing as of 2007 is the GALE project, which involves both speech recognition and translation components).

In terms of freely available resources, Carnegie Mellon University's Sphinx toolkit is one place to start to both learn about speech recognition and to start experimenting. Another resource (free as in free beer, not as in free speech) is the HTK book (and the accompanying HTK toolkit). The AT&T libraries GRM library, and DCD library are also general software libraries for large-vocabulary speech recognition.

For more software resources, see List of speech recognition software.

A useful review of the area of robustness in ASR is provided by Junqua and Haton (1995).