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11: Grundlagen der Automatischen Spracherkennung, Vorlesung, WS 2017/18, 29.11.2017
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Kandungan disediakan oleh Karlsruher Institut für Technologie (KIT). Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh Karlsruher Institut für Technologie (KIT) atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.
11 | 0:00:00 Starten 0:00:31 Die Fundamentalformel (Erinnerung) 0:01:00 Hidden Markov Model Ansatz 0:04:14 Münzen-Beispiel 0:10:53 Urne Ball Modell 0:12:02 HMM Definition 0:14:06 HMM Beobachtungsgenerierung 0:16:13 Die HMM Trellis 0:17:05 Die drei Probleme der HMMs 0:22:46 Forward Algorithmus 0:39:03 Backward Algorithmus 0:41:01 Das Decoding Problem 0:43:10 Viterbi-Algorithmus 0:45:37 Das Lern-Problem 0:53:19 Baum-Welch Regeln 0:56:57 Literatur 0:59:11 Maximum-Likelihood Methode 1:30:33 Exspectation Maximization (EM)
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