In this work a Gaussian Hidden Markov Model (GHMM) based automatic sign language recognition system is built on the SIGNUM database. The system is trained on appearance-based feat...
The next big step in embedded, mobile speech recognition will be to allow completely free input as it is needed for messaging like SMS or email. However, unconstrained dictation r...
Michael Feld, Saeedeh Momtazi, Farina Freigang, Di...
We propose a new transform speech codec that jointly encodes a wideband waveform and its corresponding wideband and narrowband speech recognition features. For distributed speech ...
Xing Fan, Michael L. Seltzer, Jasha Droppo, Henriq...
Speech translation (ST) is an enabling technology for cross-lingual oral communication. A ST system consists of two major components: an automatic speech recognizer (ASR) and a ma...
Recognizer Output Voting Error Reduction (ROVER), is a well-known procedure for decoders’ combination aiming at reducing the Word Error Rate (WER) in transcription applications....
Polish is a synthetic language with a high morpheme-perword ratio. It makes use of a high degree of inflection leading to high out-of-vocabulary (OOV) rates, and high Language Mo...
M. Ali Basha Shaik, Amr El-Desoky Mousa, Ralf Schl...
In this paper we present a number of improvements that were recently made to the template based speech recognition system developed at ESAT. Combining these improvements resulted ...
Kris Demuynck, Dino Seppi, Hugo Van hamme, Dirk Va...
In this paper we describe and analyze a data pruning method in combination with template-based automatic speech recognition. We demonstrate the positive effects of polishing the t...
We demonstrate that transformation-based learning can be used to correct noisy speech recognition transcripts in the lecture domain with an average word error rate reduction of 12...
In this work, we try a hybrid methodology for language modeling where both morphological decomposition and factored language modeling (FLM) are exploited to deal with the complex ...