Anzeige
Erschienen in:
2007 | OriginalPaper | Buchkapitel
Towards Automatic Transcription of Large Spoken Archives in Agglutinating Languages – Hungarian ASR for the MALACH Project
verfasst von : Péter Mihajlik, Tibor Fegyó, Bottyán Németh, Zoltán Tüske, Viktor Trón
Erschienen in: Text, Speech and Dialogue
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
The paper describes automatic speech recognition experiments and results on the spontaneous Hungarian MALACH speech corpus. A novel morph-based lexical modeling approach is compared to the traditional word-based one and to another, previously best performing morph-based one in terms of word and letter error rates. The applied language and acoustic modeling techniques are also detailed. Using unsupervised speaker adaptations along with morph based lexical models 14.4%-8.1% absolute word error rate reductions have been achieved on a 2 speakers, 2 hours test set as compared to the speaker independent baseline results.