✦ LIBER ✦

Modeling lexical stress in continuous speech recognition for Dutch

✍ Scribed by Henk van den Heuvel; David van Kuijk; Lou Boves

Book ID: 108410655
Publisher: Elsevier Science
Year: 2003
Tongue: English
Weight: 154 KB
Volume: 40
Category: Article
ISSN: 0167-6393
DOI: 10.1016/s0167-6393(02)00085-7

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Audio-visual speech modeling for continu

Audio-visual speech modeling for continuous speech recognition

✍ Dupont, S.; Luettin, J. 📂 Article 📅 2000 🏛 IEEE 🌐 English ⚖ 529 KB

Tone Modeling for Continuous Mandarin Sp

Tone Modeling for Continuous Mandarin Speech Recognition

✍ Yang Cao; Shuwu Zhang; Taiyi Huang; Bo Xu 📂 Article 📅 2004 🏛 Springer US 🌐 English ⚖ 112 KB

Acoustic characteristics of lexical stre

Acoustic characteristics of lexical stress in continuous telephone speech

✍ David van Kuijk; Loe Boves 📂 Article 📅 1999 🏛 Elsevier Science 🌐 English ⚖ 336 KB

HMM/ANN hybrid model for continuous Mala

HMM/ANN hybrid model for continuous Malayalam speech recognition

✍ Anuj Mohamed; K.N. Ramachandran Nair 📂 Article 📅 2012 🏛 Elsevier 🌐 English ⚖ 773 KB

Word juncture modeling using phonologica

Word juncture modeling using phonological rules for HMM-based continuous speech recognition

✍ Egidio P. Giachin; Aaron E. Rosenberg; Chin-Hui Lee 📂 Article 📅 1991 🏛 Elsevier Science 🌐 English ⚖ 893 KB

Continuously variable duration hidden Ma

Continuously variable duration hidden Markov models for automatic speech recognition

✍ S.E. Levinson 📂 Article 📅 1986 🏛 Elsevier Science 🌐 English ⚖ 655 KB

During tile past decade, the applicability of hidden Markov models (HMM) to various facets of speech analysi s has been demonstrated in several different experiments. These investigations all rest on the assumption that speech is a quasi-stationary process whose stationary intervals can be identifie