An investigation of subspace modeling for phonetic and speaker variability in automatic speech recognition

This paper investigates the impact of sub space based techniques for acoustic modeling in automatic speech recognition (ASR). There are many well known approaches to subspace based speaker adaptation which represent sources of variability as a projection within a low dimensional subspace. A new appr...

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Bibliographische Detailangaben

Hauptverfasser:	Rose, Richard, Shou-Chun Yin, Yun Tang
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Acoustics Adaptation models automated speech recognition Equations Hidden Markov models Mathematical model Speech recognition Training
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