Regarding the impact of Kazakh phonetic transcription on the performance of automatic speech recognition systems

Abstract

Over the past decades automatic speech recognition has made remarkable advances, in both theoretical and practical aspects. Evolution of research in this field has been proceeding from the recognition of individual sounds and phonemes to the recognition of continuous and mixed speech, including tasks of automatic transcription of broadcast news and telephone conversations. Despite the high performance of continuous speech recognition systems, which makes up to 95%, the performance of phoneme recognition systems remains below 85%. However, phoneme recognition is widely used in a number of applications, such as spoken term detection, language identification, speaker identification and others. The paper presents the results of the experiments on continuous Kazakh speech recognition using different phoneme sets and alternative phonetic transcriptions. This study was instigated by the fact that in modern Kazakh linguistics there is no common agreement about the phonetic system of the Kazakh language, while the list of phonemes and their number noticeably vary in different textbooks. Therefore, we aimed our experiments to study the impact of the phonetic system of the language, its orthoepic rules and the corresponding phonetic transcriptions on the performance of the phoneme recognition systems, which are the initial stage in the general systems of continuous speech recognition. The following 6 systems of phonetic transcription have been considered and tested in our study. The fi rst one is a project of the new Kazakh alphabet and a set of spelling rules proposed by Prof. A. Sharipbay. The second system is a set of orthoepic rules for the actual Kazakh Cyrillic alphabet, introduced by Kazakh linguists – the authors of the Kazakh “Orthoepical Dictionary”. The third one of the systems considered is a phonetic system and a set of empirical transcription rules used by the authors of this work in their studies...