This work proposes a method of speech enhancement that uses a network of HMMs to first decode noisy speech and to then synthesise a set of features that enables a clean speech signal to be reconstructed. Different choices of acoustic model (whole-word, monophone and triphone) and grammars (highly constrained to no constraints) are considered and the effects of introducing or relaxing acoustic and grammar constraints investigated. For robust operation in noisy conditions it is necessary for the HMMs to model noisy speech and consequently noise adaptation is investigated along with its effect on the reconstructed speech. Speech quality and intelligibility analysis find triphone models with no grammar, combined with noise adaptation, gives highest performance that outperforms conventional methods of enhancement at low signal-to-noise ratios.
|Title of host publication||Proceedings of the Interspeech Conference 2016|
|Publisher||International Speech Communication Association|
|Number of pages||5|
|Publication status||Published - Sep 2016|
|Event||Interspeech 2016 - San Francisco, United States|
Duration: 8 Sep 2016 → 12 Sep 2016
|Period||8/09/16 → 12/09/16|