Front-end for Far-field Speech Recognition based on Frequency Domain Linear Prediction
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In this paper we investigate the possibility of improving the speech recognition performance of meeting recordings by using slides captured during the recording process. The key hypothesis exploited in this work is that both slides and speech carry correla ...
This work presents categorization experiments performed over noisy texts. By noisy it is meant any text obtained through an extraction process (affected by errors) from media other than digital texts (e.g. transcriptions of speech recordings extracted with ...
This work presents categorization experiments performed over noisy texts. By noisy it is meant any text obtained through an extraction process (affected by errors) from media other than digital texts (e.g. transcriptions of speech recordings extracted with ...
Speaker detection is an important component of a speech-based user interface. Audiovisual speaker detection, speech and speaker recognition or speech synthesis for example find multiple applications in human-computer interaction, multimedia content indexin ...
The goal of this thesis is to develop and design new feature representations that can improve the automatic speech recognition (ASR) performance in clean as well noisy conditions. One of the main shortcomings of the fixed scale (typically 20-30 ms long ana ...
\begin{abstract} In this paper, we address an adaptive beamforming application in realistic acoustic conditions. After the position of a speaker is estimated by a speaker tracking system, we construct a subband-domain beamformer in \emph{generalized sidelo ...
In this paper, we address an adaptive beamforming application in realistic acoustic conditions. After the position of a speaker is estimated by a speaker tracking system, we construct a subband-domain beamformer in generalized sidelobe canceller (GSC) conf ...
In this paper, we investigate the possibility of enhancing state-of-the-art HMM-based speech recognition systems using data-driven techniques, where whole set of training utterances is used as reference models and recognition is then performed through the ...
In this paper, we investigate the possibility of enhancing state-of-the-art HMM-based speech recognition systems using data-driven techniques, where whole set of training utterances is used as reference models and recognition is then performed through the ...
In this work, we consider an acoustic beamforming application where two speakers are simultaneously active. We construct one subband-domain beamformer in \emph{generalized sidelobe canceller} (GSC) configuration for each source. In contrast to normal pract ...
