Structural Representation of Speech for Phonetic Classification

This paper explores the issues involved in using symbolic metric algorithms for automatic speech recognition (ASR), via a structural representation of speech. This representation is based on a set of phonological distinctive features which is a linguistically well-motivated alternative to the "beads-on-a-string" view of speech that is standard in current ASR systems. We report the promising results of phoneme classification experiments conducted on a standard continuous speech task.

• Type: Conference
• Year: 2004
• Where: ICPR
• Authors: Alexander Gutkin, Simon King
• Keywords: Automatic Speech Recognition, Computer Vision, Current Asr Systems, ICPR 2004, Standard Continuous Speech