Phonetic transcription in automatic speech recognition

Abstract

This paper discusses automatic phonetic transcription to be applied in Hungarian speech recognition. It first deals with the basic technologies of automatic speech recognition (ASR) for the sake of readers not familiar with this scientific field, then it discusses the place of (automatic) phonetic transcription in ASR. After that, our method developed for transcribing Hungarian texts automatically is introduced. This technique is an extension of the traditional linear transcription approach; its output is called 'optioned' because it contains pronunciation options in parallel arcs. We present our experiences with promising improvements in recogniser training efficiency. The achievements are due to the application of deeper linguistic (phonological) knowledge. With the training technique developed not only the quality of the acoustic models can be enhanced, but also, at the same time, the amount of the required manual work can effectively be decreased.

Morphology aware data augmentation with neural language models for online hybrid ASR

“…In Hungarian there is a close correspondence between the surface (orthographic) form of words and their phonetic transcription, therefore the pronunciation of most words can be derived by using simple grapheme-phoneme mapping rules (Mihajlik et al 2002). However, there are always exceptions e.g.…”

Corpus-Based Unit Selection TTS for Hungarian

“…To mark the sound boundaries in the speech waveform, a Hungarian speech recognizer was used in forced alignment mode [5]. We performed a manual text normalization by expanding numbers, signs, and abbreviations in the textual form of the sentences before and during the recording.…”