%0 Journal Article %1 Hueber2010-cm %A Hueber, Thomas %A Benaroya, Elie-Laurent %A Chollet, Gérard %A Denby, Bruce %A Dreyfus, Gérard %A Stone, Maureen %D 2010 %J Speech Commun. %K Corpus-based Silent Ultrasound; Visual phone recognition;subvocal speech speech; synthesis; %N 4 %P 288--300 %T Development of a silent speech interface driven by ultrasound and optical images of the tongue and lips %V 52 %X This article presents a segmental vocoder driven by ultrasound and optical images (standard CCD camera) of the tongue and lips for a ``silent speech interface'' application, usable either by a laryngectomized patient or for silent communication. The system is built around an audio--visual dictionary which associates visual to acoustic observations for each phonetic class. Visual features are extracted from ultrasound images of the tongue and from video images of the lips using a PCA-based image coding technique. Visual observations of each phonetic class are modeled by continuous HMMs. The system then combines a phone recognition stage with corpus-based synthesis. In the recognition stage, the visual HMMs are used to identify phonetic targets in a sequence of visual features. In the synthesis stage, these phonetic targets constrain the dictionary search for the sequence of diphones that maximizes similarity to the input test data in the visual space, subject to a concatenation cost in the acoustic domain. A prosody-template is extracted from the training corpus, and the final speech waveform is generated using ``Harmonic plus Noise Model'' concatenative synthesis techniques. Experimental results are based on an audiovisual database containing 1h of continuous speech from each of two speakers.

@article{Hueber2010-cm, abstract = {This article presents a segmental vocoder driven by ultrasound and optical images (standard CCD camera) of the tongue and lips for a ``silent speech interface'' application, usable either by a laryngectomized patient or for silent communication. The system is built around an audio--visual dictionary which associates visual to acoustic observations for each phonetic class. Visual features are extracted from ultrasound images of the tongue and from video images of the lips using a PCA-based image coding technique. Visual observations of each phonetic class are modeled by continuous HMMs. The system then combines a phone recognition stage with corpus-based synthesis. In the recognition stage, the visual HMMs are used to identify phonetic targets in a sequence of visual features. In the synthesis stage, these phonetic targets constrain the dictionary search for the sequence of diphones that maximizes similarity to the input test data in the visual space, subject to a concatenation cost in the acoustic domain. A prosody-template is extracted from the training corpus, and the final speech waveform is generated using ``Harmonic plus Noise Model'' concatenative synthesis techniques. Experimental results are based on an audiovisual database containing 1h of continuous speech from each of two speakers.}, added-at = {2023-06-06T00:19:46.000+0200}, author = {Hueber, Thomas and Benaroya, Elie-Laurent and Chollet, G{\'e}rard and Denby, Bruce and Dreyfus, G{\'e}rard and Stone, Maureen}, biburl = {https://www.bibsonomy.org/bibtex/2861b93254e48c902cbdcfe92a69f2d3e/willwade}, interhash = {ad81f36f82321e65b8ef68f15cc35043}, intrahash = {861b93254e48c902cbdcfe92a69f2d3e}, journal = {Speech Commun.}, keywords = {Corpus-based Silent Ultrasound; Visual phone recognition;subvocal speech speech; synthesis;}, month = apr, number = 4, pages = {288--300}, timestamp = {2023-06-06T00:20:15.000+0200}, title = {Development of a silent speech interface driven by ultrasound and optical images of the tongue and lips}, volume = 52, year = 2010 }