Add to ORKGMaximum a posteriori adaptation of subspace Gaussian mixture models for cross-lingual speech recognition Citation for published version
Summarization: A trend in automatic speech recognition systems is the use of continuous mixture-dens...
1. Objective Intelligibility Measures Based on Mutual Information for Speech Subjected to Speech Enh...
Summarization: The porting of a speech recognition system to a new language is usually a time-consum...
This paper concerns cross-lingual acoustic modeling in the case when there are limited target langua...
This thesis has been submitted in fulfilment of the requirements for a postgraduate degree (e.g. PhD...
This paper studies cross-lingual acoustic modeling in the context of subspace Gaussian mixture model...
Multilingual speech recognition is increasingly gaining attention for in-car speech controlled appli...
Noise adaptive training for subspace Gaussian mixture models Citation for published version
The subspace Gaussian mixture model (SGMM) has been exploited for cross-lingual speech recognition. ...
Although research has previously been done on multilingual speech recognition, it has been found to ...
Abstract—We investigate cross-lingual acoustic modelling for low resource languages using the subspa...
Recent studies have shown that speech recognizers may benefit from data in languages other than the ...
This paper investigates employment of Subspace Gaussian Mixture Models (SGMMs) for acoustic model ad...
The subspace Gaussian mixture model (SGMM) has been recently proposed as an acoustic modeling techni...
In conventional hidden Markov model (HMM) based speech recognisers, the emitting HMM states are mode...
Summarization: A trend in automatic speech recognition systems is the use of continuous mixture-dens...
1. Objective Intelligibility Measures Based on Mutual Information for Speech Subjected to Speech Enh...
Summarization: The porting of a speech recognition system to a new language is usually a time-consum...
This paper concerns cross-lingual acoustic modeling in the case when there are limited target langua...
This thesis has been submitted in fulfilment of the requirements for a postgraduate degree (e.g. PhD...
This paper studies cross-lingual acoustic modeling in the context of subspace Gaussian mixture model...
Multilingual speech recognition is increasingly gaining attention for in-car speech controlled appli...
Noise adaptive training for subspace Gaussian mixture models Citation for published version
The subspace Gaussian mixture model (SGMM) has been exploited for cross-lingual speech recognition. ...
Although research has previously been done on multilingual speech recognition, it has been found to ...
Abstract—We investigate cross-lingual acoustic modelling for low resource languages using the subspa...
Recent studies have shown that speech recognizers may benefit from data in languages other than the ...
This paper investigates employment of Subspace Gaussian Mixture Models (SGMMs) for acoustic model ad...
The subspace Gaussian mixture model (SGMM) has been recently proposed as an acoustic modeling techni...
In conventional hidden Markov model (HMM) based speech recognisers, the emitting HMM states are mode...
Summarization: A trend in automatic speech recognition systems is the use of continuous mixture-dens...
1. Objective Intelligibility Measures Based on Mutual Information for Speech Subjected to Speech Enh...
Summarization: The porting of a speech recognition system to a new language is usually a time-consum...