✦ LIBER ✦

Hidden Markov model classification of myoelectric signals in speech

✍ Scribed by Chan, A.D.C.; Englehart, K.; Hudgins, B.; Lovely, D.F.

Book ID: 114580160
Publisher: IEEE
Year: 2002
Tongue: English
Weight: 938 KB
Volume: 21
Category: Article
ISSN: 0739-5175
DOI: 10.1109/memb.2002.1044184

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Hidden Gauss-Markov models for signal cl

Hidden Gauss-Markov models for signal classification

✍ Ainsleigh, P.L.; Kehtarnavaz, N.; Streit, R.L. 📂 Article 📅 2002 🏛 IEEE 🌐 English ⚖ 428 KB

Semi-continuous hidden Markov models for

Semi-continuous hidden Markov models for speech signals

✍ X.D. Huang; M.A. Jack 📂 Article 📅 1989 🏛 Elsevier Science 🌐 English ⚖ 993 KB

Classification of Seismic Volcanic Signa

Classification of Seismic Volcanic Signals Using Hidden-Markov-Model-Based Generative Embeddings

✍ Bicego, Manuele; Acosta-Munoz, Carolina; Orozco-Alzate, Mauricio 📂 Article 📅 2013 🏛 IEEE 🌐 English ⚖ 754 KB

N-channel hidden Markov models for combi

N-channel hidden Markov models for combined stressed speech classification and recognition

✍ Womack, B.D.; Hansen, J.H.L. 📂 Article 📅 1999 🏛 IEEE 🌐 English ⚖ 256 KB

Classification of internal carotid arter

Classification of internal carotid artery Doppler signals using fuzzy discrete hidden Markov model

✍ Harun Uğuz; Halife Kodaz 📂 Article 📅 2011 🏛 Elsevier Science 🌐 English ⚖ 640 KB

State clustering in hidden Markov model-

State clustering in hidden Markov model-based continuous speech recognition

✍ S.J. Young; P.C. Woodland 📂 Article 📅 1994 🏛 Elsevier Science 🌐 English ⚖ 535 KB

A key problem in the use of context-dependent hidden Markov models is the need to balance the desired model complexity with the amount of available training data. This paper describes a method which uses a simple agglomerative algorithm to cluster and tie acoustically similar states. The main proper