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A three-dimensional (3-D) image-compression algorithm based on integer wavelet transforms and zerotree coding is presented. The embedded coding of zerotrees of wavelet coefficients (EZW) algorithm is extended to three dimensions, and context-based adaptive arithmetic coding is used to improve its performance. The resultant algorithm, 3-D CB-EZW, efficiently(More)
In recent years there has been growing interest in discriminative parameter training techniques, resulting from notable improvements in speech recognition performance on tasks ranging in size from digit recognition to Switchboard. Typified by Maximum Mutual Information (MMI) or Minimum Classification Error (MCE) training, these methods assume a fixed(More)
TC-STAR is an European Union funded speech to speech translation project to transcribe, translate and synthesize European Parliamentary Plenary Speeches (EPPS). This paper describes IBM’s English and Spanish speech recognition systems submitted to the TC-STAR 2006 Evaluation. The technical advances in this submission include two different algorithms for(More)
In this paper we report recent improvements in word error performance on a voicemail transcription task. Last year, the speaker independent word error rate (WER) on the dev test set of the Voicemail Transcription task was reported at 35.45% [1]. This year, we report a relative 20% gain over this number. The improvements were obtained using several new(More)
{ 1 Research in the speech recognition speech-to-text conversion) area has been underway for a couple of decades, and a great deal of progress has been made in reducing the word error rate (WER). In this paper, we attempt to summarize the state of the art in speech recognition algorithms. The algorithms we describe span the areas of lexicon design, feature(More)
In recent years there has been growing interest in discriminative parameter training techniques, resulting from notable improvements in speech recognition performance on tasks ranging in size from digit recognition to Switchboard. Typified by Maximum Mutual Information (MMI) or Minimum Classification Error (MCE) training, these methods assume a fixed(More)
' Research in the speech recognition speech-to-text conversion) area hus been underway for a couple of decades, and a greal deal of progress has been made in reducing the word error rate (WER). In this paper, we attempt to summarize the state of the art in speech recognition algorithms. The algorithms we describe span the areas of lexicon design, feature(More)
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